{"meta":{"query_hash":"9e6804b4b067","filters":{"venue":"International Journal of Software Science and Computational Intelligence"},"cohort_total":66,"direct_labels_cover":0,"predictions_cover":66,"exported":66,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/9e6804b4b067","api":"https://metacan.xera.ac/api/v1/cohort?venue=International+Journal+of+Software+Science+and+Computational+Intelligence"},"results":[{"id":"W1098745260","doi":"10.4018/ijssci.2014100101","title":"Human Cognition in Automated Truing Test Design","year":2014,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; CAPTCHA; The Internet; Usability; World Wide Web; Readability; Web service; Computer security; Human–computer interaction","score_opus":0.03175677535882087,"score_gpt":0.3186879811740916,"score_spread":0.2869312058152707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1098745260","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2209642,0.001989288,0.711573,0.002871915,0.00017361439,0.0009000951,0.00009727003,0.001984533,0.059446093],"genre_scores_gemma":[0.8735944,0.00028147898,0.123595096,0.00039313763,0.00003508189,0.00028860066,0.00006649797,0.00008139129,0.0016642266],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9803647,0.0152415335,0.00064741896,0.0013747278,0.0018463559,0.00052524125],"domain_scores_gemma":[0.93258804,0.055741698,0.0027559306,0.0038592736,0.0041215434,0.00093347137],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0153650455,0.00095076615,0.00057777256,0.0020948339,0.00084344484,0.0055367607,0.0019022269,0.0016920351,0.0056042676],"category_scores_gemma":[0.08584567,0.0004919228,0.00071557367,0.00071151607,0.005244371,0.003832629,0.0015678349,0.0010939289,0.00074302003],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009386406,0.0009894219,0.032164987,0.0012876084,0.00034981102,0.0005830181,0.012916597,0.06906514,0.014086551,0.12669916,0.006535832,0.7343832],"study_design_scores_gemma":[0.000576009,0.0020467385,0.042490315,0.0005862964,0.00027002845,0.0011380125,0.0079251565,0.45623404,0.019522928,0.43645352,0.03233558,0.0004214208],"about_ca_topic_score_codex":0.006122215,"about_ca_topic_score_gemma":0.0037412415,"teacher_disagreement_score":0.0153650455,"about_ca_system_score_codex":0.003029259,"about_ca_system_score_gemma":0.0021115467,"threshold_uncertainty_score":0.08125913},"labels":[],"label_agreement":null},{"id":"W1967132902","doi":"10.4018/jssci.2010040101","title":"Multi-Fractal Analysis for Feature Extraction from DNA Sequences","year":2010,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Fractal and DNA sequence analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Fractal; Fractal dimension; Computer science; Sequence (biology); Pattern recognition (psychology); Fractal analysis; Coding (social sciences); Artificial intelligence; Algorithm; Mathematics; Biology; Statistics; Genetics; Mathematical analysis","score_opus":0.016200363577125093,"score_gpt":0.3238396650266179,"score_spread":0.3076393014494928,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1967132902","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012202093,0.00051891996,0.98608994,0.000059805145,0.000019748142,0.000025577621,0.000099086916,0.00062319194,0.00036160005],"genre_scores_gemma":[0.21332431,0.0006266661,0.7845922,0.00004292483,0.000049381768,0.0001258588,0.00044622776,0.00011747989,0.0006748635],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995401,0.00010469744,0.000037579743,0.00008628167,0.00020052155,0.000030929004],"domain_scores_gemma":[0.9987369,0.0007463842,0.00014648063,0.00011073748,0.00022716979,0.000032344524],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006556179,0.00054547074,0.0005516628,0.0025367478,0.00024842826,0.0006416613,0.00044499905,0.00049003016,0.0010714362],"category_scores_gemma":[0.0032540592,0.00022973768,0.00078640593,0.001292303,0.00036759482,0.0008615457,0.00040340153,0.0005990732,0.00061796966],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001825932,0.000050879018,0.0021087911,0.00045809374,0.00012545318,0.00023071312,0.00027695636,0.074728645,0.14971799,0.020079149,0.0021612407,0.7498794],"study_design_scores_gemma":[0.000018451325,0.000112532456,0.004517277,0.00004727149,0.00004605928,0.00048304873,0.00005658439,0.92722106,0.04209886,0.015553549,0.009772403,0.00007284187],"about_ca_topic_score_codex":0.0007815627,"about_ca_topic_score_gemma":0.00057740725,"teacher_disagreement_score":0.0025367478,"about_ca_system_score_codex":0.00041063866,"about_ca_system_score_gemma":0.00030773573,"threshold_uncertainty_score":0.0035842657},"labels":[],"label_agreement":null},{"id":"W1971616252","doi":"10.4018/ijssci.2013010103","title":"The Cognitive Process and Formal Models of Human Attentions","year":2013,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Cognition; Cognitive computing; Cognitive robotics; Process (computing); Perception; Cognitive science; Consciousness; Cognitive model; Artificial intelligence; Human–computer interaction; Rational analysis; Embodied cognition; Psychology","score_opus":0.026990721898201724,"score_gpt":0.3204896401720948,"score_spread":0.2934989182738931,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1971616252","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029190553,0.00295016,0.8971284,0.0058597936,0.00015680476,0.00008503833,0.00020021693,0.0003131079,0.064116016],"genre_scores_gemma":[0.84403586,0.0020727972,0.14181282,0.00071227504,0.00039263922,0.00045807418,0.00021423548,0.00008882096,0.010212658],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9978567,0.0008440128,0.0001400286,0.00036822585,0.0005466486,0.00024446333],"domain_scores_gemma":[0.9962463,0.0023537094,0.00030846478,0.0004740448,0.00044914457,0.00016839131],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024587475,0.00077464624,0.00053239695,0.0016112921,0.0011784575,0.0035170757,0.0017035146,0.0017994428,0.0043796077],"category_scores_gemma":[0.0078021083,0.00040618223,0.0016643134,0.0010497611,0.007959995,0.0070011034,0.00218707,0.002078364,0.0006032194],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003587963,0.000004494288,0.000038341164,0.000015839896,0.0000033857307,0.000019087765,0.00017956068,0.0020572331,0.000094827345,0.99613166,0.00015401116,0.001297944],"study_design_scores_gemma":[0.00001013811,0.000008736882,0.00007062039,0.000016368504,0.0000062859694,0.00002994893,0.00004777093,0.01421999,0.00009592389,0.9824927,0.00299491,0.00000651752],"about_ca_topic_score_codex":0.0055289213,"about_ca_topic_score_gemma":0.0021530914,"teacher_disagreement_score":0.0055289213,"about_ca_system_score_codex":0.0028074607,"about_ca_system_score_gemma":0.0018108943,"threshold_uncertainty_score":0.02036959},"labels":[],"label_agreement":null},{"id":"W1973213711","doi":"10.4018/jssci.2012100105","title":"Formal Rules for Fuzzy Causal Analyses and Fuzzy Inferences","year":2012,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Fuzzy cognitive map; Artificial intelligence; Computational intelligence; Fuzzy logic; Deductive reasoning; Semantics (computer science); Inference; Fuzzy set; Fuzzy set operations; Theoretical computer science; Programming language","score_opus":0.07040909901516905,"score_gpt":0.3738101542913642,"score_spread":0.30340105527619515,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973213711","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016696277,0.00029873318,0.98590904,0.00095746986,0.0001906172,0.00024351545,0.0002830764,0.00041670454,0.010031108],"genre_scores_gemma":[0.05777282,0.00058161665,0.9367985,0.00047071028,0.00021031238,0.0005800162,0.00042726638,0.00011922777,0.0030394557],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9914561,0.0027132286,0.0013257439,0.001212343,0.0028406905,0.00045181357],"domain_scores_gemma":[0.98493874,0.009713076,0.0011502702,0.0016875528,0.0023212705,0.00018902696],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013002144,0.0010968633,0.0008456732,0.003768028,0.0023151569,0.0050260667,0.0028866122,0.0024194745,0.0067138346],"category_scores_gemma":[0.024053894,0.0008648616,0.0032612698,0.0018214241,0.007403515,0.0064492086,0.0022218376,0.004880725,0.0020164906],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013210446,0.000026037644,0.00012092018,0.000095554984,0.000022551847,0.00014144527,0.0004184463,0.0046588173,0.0004981865,0.97800225,0.0016163674,0.014386239],"study_design_scores_gemma":[0.00003616434,0.000013129821,0.00006154508,0.00012512211,0.000039486295,0.00014042082,0.000095202595,0.019317502,0.0014539281,0.94842666,0.030258244,0.000032620483],"about_ca_topic_score_codex":0.005243162,"about_ca_topic_score_gemma":0.0049702046,"teacher_disagreement_score":0.013002144,"about_ca_system_score_codex":0.0024100486,"about_ca_system_score_gemma":0.0029953897,"threshold_uncertainty_score":0.06876272},"labels":[],"label_agreement":null},{"id":"W1977983630","doi":"10.4018/ijssci.2013040103","title":"A Formal Knowledge Retrieval System for Cognitive Computers and Cognitive Robotics","year":2013,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Knowledge base; Cognitive robotics; Artificial intelligence; Process (computing); Cognition; Set (abstract data type); Cognitive model; Robotics; Knowledge retrieval; Cognitive computing; Human–computer interaction; Knowledge extraction; Robot; Programming language","score_opus":0.024240243155446543,"score_gpt":0.302676525118646,"score_spread":0.2784362819631995,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977983630","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0060242633,0.00014338734,0.98021644,0.00040780267,0.00007740731,0.00016359896,0.00016667173,0.00615028,0.0066502034],"genre_scores_gemma":[0.17100866,0.00028629554,0.81745803,0.00038832508,0.00012028383,0.00036358097,0.00076858007,0.00035599366,0.009250211],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988205,0.00027322987,0.00013181813,0.00028314497,0.00039648777,0.00009481791],"domain_scores_gemma":[0.99869174,0.00041967642,0.00010891824,0.00036774564,0.0003271833,0.00008481315],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019684732,0.0005188593,0.00055914465,0.0015806794,0.0011309001,0.002999813,0.0019084447,0.0012271028,0.00745975],"category_scores_gemma":[0.004800101,0.00038356284,0.0012635425,0.00089616666,0.0018324142,0.006016677,0.0021735611,0.0015792144,0.002433135],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012771977,0.00012911196,0.00062474434,0.0003180005,0.00006401242,0.00028176102,0.0008333532,0.017608063,0.0191585,0.78993106,0.008498545,0.16242512],"study_design_scores_gemma":[0.00013825369,0.00023837917,0.0005918589,0.00018130365,0.00018082326,0.00077079254,0.0002817657,0.3833753,0.027472438,0.41869283,0.1679485,0.000127766],"about_ca_topic_score_codex":0.003735537,"about_ca_topic_score_gemma":0.0028567882,"teacher_disagreement_score":0.00745975,"about_ca_system_score_codex":0.0018799728,"about_ca_system_score_gemma":0.0035829556,"threshold_uncertainty_score":0.024955392},"labels":[],"label_agreement":null},{"id":"W1980301902","doi":"10.4018/jssci.2010101907","title":"The Formal Design Model of an Automatic Teller Machine (ATM)","year":2010,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Japan Society for the Promotion of Science","keywords":"Computer science; Formal specification; Process (computing); Formal methods; Programming language; Code generation; Software engineering; Operating system; Key (lock)","score_opus":0.02828604973800589,"score_gpt":0.30089107594008935,"score_spread":0.27260502620208343,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980301902","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010622126,0.00048429106,0.96899664,0.0009771652,0.00012989303,0.00014290673,0.00024723625,0.0006498419,0.017749818],"genre_scores_gemma":[0.28073254,0.0012184435,0.6953585,0.00058311777,0.00017066195,0.00075607083,0.000631051,0.0002004951,0.020349147],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987153,0.0003690821,0.00011890704,0.00019659913,0.00048765668,0.00011248362],"domain_scores_gemma":[0.99895704,0.0004798778,0.00012364419,0.0001677987,0.00022799498,0.00004361007],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016726459,0.0005244961,0.0003001012,0.0006133783,0.0007347262,0.0020290106,0.0011561762,0.0011792948,0.0033981316],"category_scores_gemma":[0.0023036352,0.00044857123,0.0010931253,0.0004797866,0.0023873239,0.0026440383,0.00083857484,0.001614996,0.00094800955],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025705185,0.000027161663,0.00015265903,0.00011670177,0.000009455923,0.00021300482,0.000343513,0.019124392,0.0043368055,0.9619597,0.0013093958,0.012381584],"study_design_scores_gemma":[0.00011953926,0.00022929999,0.00029747956,0.00023942636,0.000091126196,0.0008352068,0.00029338093,0.19690451,0.014803428,0.54035,0.24576849,0.00006808913],"about_ca_topic_score_codex":0.0038639195,"about_ca_topic_score_gemma":0.0023981973,"teacher_disagreement_score":0.0038639195,"about_ca_system_score_codex":0.0015307079,"about_ca_system_score_gemma":0.0029040966,"threshold_uncertainty_score":0.011367857},"labels":[],"label_agreement":null},{"id":"W1982616249","doi":"10.4018/jssci.2010070106","title":"The Formal Design Model of a Real-Time Operating System (RTOS+)","year":2010,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Advanced Micro Devices","keywords":"Real-time operating system; Computer science; Process (computing); Embedded system; Set (abstract data type); Operating system; Programming language","score_opus":0.025345992987034816,"score_gpt":0.2861344496472068,"score_spread":0.260788456660172,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1982616249","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0044490807,0.00045241177,0.98390466,0.0006079041,0.00016183582,0.00014064711,0.00020153244,0.0005916672,0.009490251],"genre_scores_gemma":[0.19372992,0.0017917395,0.78838056,0.00078975415,0.00026602639,0.0011639897,0.00076880114,0.00032315086,0.012786133],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99821174,0.0004919556,0.00023940142,0.00028995323,0.0006085165,0.00015834621],"domain_scores_gemma":[0.9980617,0.00083812414,0.00025361453,0.00038613702,0.00037855367,0.00008174891],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023112274,0.00080521725,0.00045158953,0.00061579514,0.00068710523,0.0028427015,0.0016197498,0.0014688448,0.0034407778],"category_scores_gemma":[0.0027603735,0.0006502058,0.0013272295,0.00049654423,0.0030555062,0.0033144006,0.0011035322,0.0025222672,0.0013230778],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003364711,0.000031737934,0.00023070768,0.00029634725,0.000015599056,0.0002232961,0.00037533932,0.02281426,0.0056425747,0.9503435,0.002081407,0.017911598],"study_design_scores_gemma":[0.00012483734,0.00030324946,0.00040206892,0.00042865227,0.000090163834,0.001014013,0.00023338872,0.15762882,0.017065858,0.45037687,0.3722522,0.00007983557],"about_ca_topic_score_codex":0.0024395694,"about_ca_topic_score_gemma":0.001485764,"teacher_disagreement_score":0.0034407778,"about_ca_system_score_codex":0.0013519877,"about_ca_system_score_gemma":0.0029138124,"threshold_uncertainty_score":0.0122231245},"labels":[],"label_agreement":null},{"id":"W1982941791","doi":"10.4018/jssci.2010040103","title":"Design and Implementation of an Autonomic Code Generator Based on RTPA","year":2010,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Programming language; Code generation; Executable; Java; Generator (circuit theory); Code (set theory); Parsing; Software; Set (abstract data type); Software engineering; Operating system","score_opus":0.023873084039368185,"score_gpt":0.32801784573137976,"score_spread":0.3041447616920116,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1982941791","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012003474,0.000045324643,0.95139503,0.00009180625,0.000053737152,0.0003640703,0.00009393804,0.033987705,0.00196499],"genre_scores_gemma":[0.22399649,0.00012650725,0.7668344,0.00023991868,0.000041703544,0.00080356374,0.0007338687,0.003044955,0.0041786693],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991178,0.00017142523,0.000095392126,0.00023407555,0.00028140866,0.00009986803],"domain_scores_gemma":[0.99818027,0.0005594823,0.00016637833,0.00044700314,0.0005375268,0.00010938728],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014173251,0.00062924717,0.0006681281,0.00079407747,0.00036734377,0.0010850991,0.0025751023,0.00075167767,0.0037194588],"category_scores_gemma":[0.0033820372,0.000606388,0.0006064946,0.0003687274,0.0006474689,0.0012254278,0.0007661376,0.0010861275,0.0016328753],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010943346,0.0008614363,0.007644195,0.00091635995,0.00028873884,0.0023412157,0.0013500979,0.1204492,0.17957439,0.073431514,0.01736532,0.5946832],"study_design_scores_gemma":[0.00040417953,0.00038921606,0.00089015154,0.00006442354,0.000101353806,0.0008024559,0.00005425016,0.8367168,0.123280376,0.00829022,0.0289276,0.00007897946],"about_ca_topic_score_codex":0.0011081188,"about_ca_topic_score_gemma":0.00064802484,"teacher_disagreement_score":0.0037194588,"about_ca_system_score_codex":0.00052092253,"about_ca_system_score_gemma":0.0012604551,"threshold_uncertainty_score":0.012442768},"labels":[],"label_agreement":null},{"id":"W1983192482","doi":"10.4018/jssci.2012070102","title":"A Novel Cross Folding Algorithm for Multimodal Cancelable Biometrics","year":2012,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Biometrics; Computer science; Pattern recognition (psychology); Artificial intelligence; Data mining; Algorithm","score_opus":0.047497525949918164,"score_gpt":0.35817766473223867,"score_spread":0.3106801387823205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1983192482","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0043321596,0.000082453975,0.99439913,0.000029990997,0.000032505406,0.00002499188,0.000012655584,0.0006380226,0.0004480246],"genre_scores_gemma":[0.07587852,0.000119042954,0.9196156,0.00010043645,0.00003853541,0.00008366728,0.00015926821,0.00016168655,0.0038431366],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99916303,0.00013558412,0.00005522913,0.00021569016,0.00036282535,0.00006761686],"domain_scores_gemma":[0.9994373,0.00013607621,0.000043248827,0.00012875833,0.00022651991,0.000028157072],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008638243,0.00083065475,0.0007810493,0.0010634358,0.0005166277,0.000768159,0.0010986363,0.00095216674,0.005116498],"category_scores_gemma":[0.0017411179,0.00031472289,0.0008009761,0.0009170334,0.00048416693,0.0009873275,0.0010893703,0.0008501638,0.0020315805],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021695631,0.000087055356,0.0005631665,0.00006170454,0.000046871297,0.00012394591,0.00007214556,0.033852614,0.08502557,0.008993413,0.0025222579,0.8684343],"study_design_scores_gemma":[0.000029940882,0.00021423276,0.0008606686,0.000013409891,0.000030433152,0.00058201246,0.000033130094,0.9276922,0.055872355,0.004693515,0.009944011,0.000034187167],"about_ca_topic_score_codex":0.001148081,"about_ca_topic_score_gemma":0.0009489761,"teacher_disagreement_score":0.005116498,"about_ca_system_score_codex":0.00038999013,"about_ca_system_score_gemma":0.00055570103,"threshold_uncertainty_score":0.017116368},"labels":[],"label_agreement":null},{"id":"W1986775633","doi":"10.4018/jssci.2009070102","title":"Challenges in the Design of Adoptive, Intelligent and Cognitive Systems","year":2009,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Cognition; Cognitive computing; Wearable computer; Perception; Consciousness; Cognitive ergonomics; Human–computer interaction; Meaning (existential); Cognitive science; Knowledge management; Psychology","score_opus":0.08571397134870196,"score_gpt":0.32734864002457265,"score_spread":0.2416346686758707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1986775633","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.046802174,0.009499853,0.7576516,0.06489531,0.00059977965,0.0010377406,0.000097375334,0.00066108844,0.11875506],"genre_scores_gemma":[0.36002147,0.004827904,0.6166931,0.0031134542,0.0003099481,0.0020451886,0.000082449165,0.00022531363,0.012681229],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9796323,0.01177284,0.0013488685,0.0016616298,0.0048736725,0.00071071973],"domain_scores_gemma":[0.98616564,0.007319075,0.0009175515,0.0023778332,0.0023849006,0.00083491765],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.025542535,0.0007399395,0.0008589788,0.0012507549,0.002247121,0.013801892,0.003785882,0.0046512145,0.0030543895],"category_scores_gemma":[0.027986849,0.0012207725,0.0008176293,0.0009360665,0.012057926,0.011700859,0.0047600497,0.003997864,0.0012626222],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025702962,0.00014574891,0.0010924092,0.00053371687,0.00005511105,0.00024480335,0.004955619,0.00881464,0.0014786775,0.91972685,0.0024548662,0.060471777],"study_design_scores_gemma":[0.00011387673,0.00020484351,0.000540783,0.00036300824,0.00006645571,0.00031684086,0.004132713,0.018876629,0.0013015002,0.83761275,0.13642232,0.000048274305],"about_ca_topic_score_codex":0.0016229717,"about_ca_topic_score_gemma":0.00187189,"teacher_disagreement_score":0.025542535,"about_ca_system_score_codex":0.0032327427,"about_ca_system_score_gemma":0.0054356335,"threshold_uncertainty_score":0.1350835},"labels":[],"label_agreement":null},{"id":"W1993257941","doi":"10.4018/jssci.2009062506","title":"The Formal Design Model of a Lift Dispatching System (LDS)","year":2009,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Lift (data mining); Software engineering; Formal specification; Process (computing); Formal methods; Process calculus; Formal verification; Programming language","score_opus":0.028336777435116235,"score_gpt":0.28804103730268293,"score_spread":0.2597042598675667,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1993257941","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0055766334,0.00014706055,0.98409176,0.00049933774,0.00007898609,0.0001552256,0.00017075466,0.0007864823,0.008493729],"genre_scores_gemma":[0.2317232,0.000680794,0.74974215,0.00046733068,0.00012994383,0.00095094735,0.00073763984,0.00030084897,0.015267121],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99845016,0.000379424,0.00016935424,0.0002556641,0.00059005036,0.00015532877],"domain_scores_gemma":[0.99873084,0.0005349936,0.0001382892,0.0002485308,0.00028701968,0.00006024274],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018732304,0.00062049914,0.00037650883,0.0007261989,0.0008149492,0.0025886332,0.0011821678,0.0012131602,0.00480384],"category_scores_gemma":[0.0025369907,0.0006487132,0.0012577933,0.00044194306,0.003080337,0.0028719925,0.0011624852,0.0018733249,0.0013449123],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000046629313,0.00004410394,0.0003651284,0.00022635149,0.000016529058,0.0004004105,0.00058821496,0.038507767,0.008478242,0.92719066,0.0022155219,0.021920389],"study_design_scores_gemma":[0.00014912453,0.00025312084,0.00038327233,0.00028698627,0.00008038515,0.0008645379,0.00037887247,0.30937815,0.019549634,0.45080468,0.21777931,0.00009197729],"about_ca_topic_score_codex":0.0038793173,"about_ca_topic_score_gemma":0.0024386158,"teacher_disagreement_score":0.00480384,"about_ca_system_score_codex":0.0016787171,"about_ca_system_score_gemma":0.003644122,"threshold_uncertainty_score":0.016070426},"labels":[],"label_agreement":null},{"id":"W2003118276","doi":"10.4018/jssci.2009062501","title":"On Visual Semantic Algebra (VSA)","year":2009,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":63,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Visual Objects; Artificial intelligence; Cognitive architecture; Object (grammar); Process (computing); Set (abstract data type); Cognition; Inference; Process calculus; Cognitive neuroscience of visual object recognition; Perception; Visual perception; Cognitive science; Pattern recognition (psychology); Theoretical computer science; Programming language","score_opus":0.016177643470673318,"score_gpt":0.3143102894051346,"score_spread":0.2981326459344613,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2003118276","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008748493,0.013778966,0.8345682,0.006890951,0.0016026304,0.00014863262,0.00057615567,0.000752349,0.13293366],"genre_scores_gemma":[0.47950673,0.0132139595,0.46096638,0.0059546945,0.0037050613,0.00091325206,0.0014900564,0.00061592634,0.033633918],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99720484,0.0010616387,0.00029335142,0.00049784564,0.0007081467,0.00023415401],"domain_scores_gemma":[0.99802977,0.0008530667,0.00015023777,0.0004509728,0.00036224173,0.00015358948],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034543788,0.0007889761,0.0010056985,0.0028464252,0.0025258919,0.0052836663,0.0017179627,0.0020147592,0.00801553],"category_scores_gemma":[0.004991062,0.00051849644,0.0019801625,0.002213813,0.011248124,0.014627231,0.0048312964,0.0050034667,0.0022781044],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000048312936,0.0000033189922,0.00002776296,0.000025318635,0.0000039743445,0.000027145476,0.00012534608,0.00023586367,0.00013957972,0.99417794,0.00077078235,0.004458135],"study_design_scores_gemma":[0.0000030899519,0.000006563775,0.00002932747,0.0000193725,0.000002711852,0.00006440513,0.000026021307,0.00094137026,0.00009627118,0.9844355,0.014368201,0.00000715133],"about_ca_topic_score_codex":0.0024359063,"about_ca_topic_score_gemma":0.0010518694,"teacher_disagreement_score":0.00801553,"about_ca_system_score_codex":0.0021294744,"about_ca_system_score_gemma":0.0017851347,"threshold_uncertainty_score":0.02681464},"labels":[],"label_agreement":null},{"id":"W2007622263","doi":"10.4018/jssci.2010100106","title":"The Formal Design Models of a Set of Abstract Data Types (ADTs)","year":2010,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Abstract data type; Programming language; Set (abstract data type); Architectural pattern; Data type; Process (computing); Software; Theoretical computer science; Software design; Software development","score_opus":0.0807480552929192,"score_gpt":0.34013980171779684,"score_spread":0.2593917464248776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007622263","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0020058798,0.00032420977,0.9939254,0.00040498906,0.00007982362,0.00012555816,0.0001940568,0.0002469261,0.0026932165],"genre_scores_gemma":[0.045832463,0.0010407269,0.94739354,0.00035416952,0.00018353094,0.0010524334,0.0006087556,0.00020164966,0.003332766],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9878862,0.0035440116,0.002002741,0.0017754395,0.004244878,0.00054682925],"domain_scores_gemma":[0.9824156,0.008136417,0.0016571338,0.0048017977,0.0026346936,0.0003543022],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011123068,0.0013153189,0.0011668679,0.0029277548,0.0018205019,0.007827542,0.004305314,0.0030443422,0.0035648053],"category_scores_gemma":[0.019197278,0.0019657754,0.00389813,0.0032580842,0.009671956,0.013790649,0.0032764205,0.0066800057,0.0014394624],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011141922,0.000017085884,0.00020141549,0.00012374118,0.000015348834,0.000070791335,0.00033644502,0.005454,0.00072066754,0.98283684,0.00066175417,0.009550741],"study_design_scores_gemma":[0.000049028815,0.00006750436,0.00014866442,0.00025404288,0.00007018869,0.00034829738,0.00020441145,0.057465155,0.0040273755,0.85059077,0.086713605,0.000060886443],"about_ca_topic_score_codex":0.0031891174,"about_ca_topic_score_gemma":0.0024798207,"teacher_disagreement_score":0.011123068,"about_ca_system_score_codex":0.0030366194,"about_ca_system_score_gemma":0.005572133,"threshold_uncertainty_score":0.058825076},"labels":[],"label_agreement":null},{"id":"W2016713259","doi":"10.4018/jssci.2010040105","title":"A Least-Laxity-First Scheduling Algorithm of Variable Time Slice for Periodic Tasks","year":2010,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nipissing University","funders":"","keywords":"Computer science; Scheduling (production processes); Algorithm; Task (project management); Dynamic priority scheduling; Earliest deadline first scheduling; Rate-monotonic scheduling; Mathematical optimization; Mathematics; Computer network; Quality of service","score_opus":0.013363273532181046,"score_gpt":0.28055006197033067,"score_spread":0.26718678843814964,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2016713259","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015665978,0.00029416714,0.981585,0.000082573104,0.00009976122,0.00010878798,0.00005625801,0.0010909026,0.0010165393],"genre_scores_gemma":[0.20756027,0.0002056384,0.7900316,0.00007754235,0.000049763163,0.0002122385,0.00025267288,0.00014405865,0.0014661443],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99966526,0.000066345405,0.000034526944,0.00007321717,0.00009705547,0.00006361485],"domain_scores_gemma":[0.9993549,0.00017294394,0.000073728006,0.00008368304,0.0002442245,0.000070565424],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00073534437,0.00067690964,0.00072204776,0.0010763434,0.0009490426,0.0006117955,0.0009944073,0.00040618802,0.0019745163],"category_scores_gemma":[0.0018366571,0.00028768284,0.00040623412,0.00092566176,0.0004162996,0.00073116604,0.00053188624,0.00066087657,0.000367199],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010568092,0.00019267587,0.0023526738,0.00033358333,0.000070337934,0.0002925188,0.0006188094,0.22393994,0.056965936,0.040522672,0.010599984,0.66305405],"study_design_scores_gemma":[0.00019432671,0.0003274259,0.0006356166,0.00003339683,0.00003738499,0.00029869413,0.00009414949,0.95519483,0.01740648,0.014515102,0.011199053,0.00006350734],"about_ca_topic_score_codex":0.004892168,"about_ca_topic_score_gemma":0.0045532146,"teacher_disagreement_score":0.004892168,"about_ca_system_score_codex":0.0007915413,"about_ca_system_score_gemma":0.0027346434,"threshold_uncertainty_score":0.009727418},"labels":[],"label_agreement":null},{"id":"W2019698643","doi":"10.4018/jssci.2012040103","title":"Cognitive Computational Models of Emotions and Affective Behaviors","year":2012,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computational model; Computer science; Cognition; Multidisciplinary approach; Cognitive computing; Subconscious; Affective computing; Cognitive model; Rational analysis; Cognitive science; Consciousness; Computational intelligence; Cognitive psychology; Cognitive robotics; Artificial intelligence; Process (computing); Psychology; Embodied cognition","score_opus":0.03477370738432911,"score_gpt":0.3263262400272099,"score_spread":0.2915525326428808,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2019698643","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.058493897,0.0053711273,0.79753995,0.007710753,0.00031060795,0.000112661684,0.0003964545,0.00040221922,0.1296623],"genre_scores_gemma":[0.87950426,0.0041340105,0.09841655,0.00063509843,0.00030907773,0.00038396276,0.0002806779,0.00007233292,0.016263947],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996537,0.00015311489,0.000016775622,0.000055909302,0.000077669174,0.000042797055],"domain_scores_gemma":[0.99930465,0.00046364113,0.000057356123,0.000053862746,0.00008110245,0.000039434155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005084962,0.0006058822,0.0004726967,0.0006224553,0.00057835906,0.0023202135,0.0011605722,0.0010115042,0.004195551],"category_scores_gemma":[0.0023699587,0.0002688658,0.0007502757,0.00051910145,0.0014819758,0.0022566433,0.00097370846,0.0011581845,0.00052430993],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025004769,0.000026033698,0.00048801576,0.00010080575,0.000036274465,0.000085303756,0.0003744988,0.09050012,0.0004977409,0.89360595,0.0016853225,0.012574982],"study_design_scores_gemma":[0.0000145935,0.000012545089,0.00035126123,0.00001876464,0.000020005626,0.000049143884,0.00009601427,0.3371124,0.00012839225,0.65667665,0.005509426,0.000010821928],"about_ca_topic_score_codex":0.0030141112,"about_ca_topic_score_gemma":0.002122745,"teacher_disagreement_score":0.004195551,"about_ca_system_score_codex":0.0009417932,"about_ca_system_score_gemma":0.0006896657,"threshold_uncertainty_score":0.014035463},"labels":[],"label_agreement":null},{"id":"W2023008574","doi":"10.4018/jssci.2012040105","title":"Seamless Implementation of a Telephone Switching System Based on Formal Specifications in RTPA","year":2012,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Process (computing); Process calculus; Interface (matter); Software engineering; Programming language; Operating system","score_opus":0.036981584055989274,"score_gpt":0.3242241145663096,"score_spread":0.28724253051032034,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2023008574","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15466893,0.00004014099,0.8327377,0.00015485186,0.000029279547,0.0003886621,0.00014158509,0.0052092974,0.006629653],"genre_scores_gemma":[0.5996714,0.00007356805,0.3946014,0.00009253402,0.000009234144,0.0005618738,0.00045337802,0.00030788963,0.0042286976],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99681276,0.0015386608,0.00021555189,0.0003001488,0.00091018993,0.00022268266],"domain_scores_gemma":[0.9949545,0.0023402956,0.00041373173,0.0014251049,0.00070566253,0.00016062275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027864964,0.00048269372,0.00032385363,0.00034958005,0.00041083776,0.0015459078,0.0012054329,0.00072215236,0.003784012],"category_scores_gemma":[0.007664105,0.00034789628,0.00048004824,0.00025266927,0.00087245024,0.0015205279,0.0011798544,0.00096513226,0.0010018178],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014452965,0.0024035107,0.008650234,0.0007596251,0.000111334404,0.0014665424,0.011846226,0.16675976,0.260723,0.1988889,0.004445003,0.34250063],"study_design_scores_gemma":[0.00038029446,0.0018574956,0.0035472212,0.0001766883,0.00012888583,0.00075707544,0.0013652821,0.77393967,0.13339436,0.02819445,0.056124706,0.0001339411],"about_ca_topic_score_codex":0.002097023,"about_ca_topic_score_gemma":0.0014760218,"teacher_disagreement_score":0.003784012,"about_ca_system_score_codex":0.00060826604,"about_ca_system_score_gemma":0.0014102323,"threshold_uncertainty_score":0.014736593},"labels":[],"label_agreement":null},{"id":"W2024911973","doi":"10.4018/jssci.2011040106","title":"The Formal Design Model of Doubly-Linked-Circular Lists (DLC-Lists)","year":2011,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Data structure; Programming language; Set (abstract data type)","score_opus":0.07648060991378004,"score_gpt":0.2980317098951163,"score_spread":0.22155109998133626,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2024911973","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010700707,0.00011933984,0.9820066,0.00029230275,0.000042293126,0.0001392183,0.00009971284,0.000804732,0.0057950458],"genre_scores_gemma":[0.26755366,0.0003803976,0.72113276,0.0003500182,0.000057467394,0.0006886784,0.0003918431,0.00027301407,0.009172122],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9973923,0.0009055435,0.0002969391,0.00040460925,0.0007632877,0.00023726621],"domain_scores_gemma":[0.9954945,0.0014839988,0.0005488736,0.001184294,0.001116329,0.00017205767],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033859403,0.00040947204,0.00027362566,0.0009856429,0.0010502938,0.0038041237,0.0020537279,0.0014511931,0.0033374655],"category_scores_gemma":[0.0052066953,0.0006112212,0.00094507687,0.000932067,0.0032271424,0.0048754914,0.0017368278,0.0013516216,0.0008370967],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002493316,0.000023587272,0.00035534447,0.00006585516,0.000006757944,0.00012587433,0.0003376585,0.014062968,0.0021125977,0.9716562,0.0007071952,0.010520982],"study_design_scores_gemma":[0.0000836447,0.0001688363,0.00022206608,0.00015457824,0.000073589996,0.00043345927,0.00030909784,0.27536327,0.016774347,0.57289773,0.13344806,0.00007137527],"about_ca_topic_score_codex":0.004359759,"about_ca_topic_score_gemma":0.0030879139,"teacher_disagreement_score":0.004359759,"about_ca_system_score_codex":0.0021230732,"about_ca_system_score_gemma":0.0031905943,"threshold_uncertainty_score":0.017906785},"labels":[],"label_agreement":null},{"id":"W2035931420","doi":"10.4018/jssci.2010100103","title":"Perspectives on Cognitive Computing and Applications","year":2010,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina; University of Alberta; University of Calgary","funders":"","keywords":"Cognitive computing; Computer science; Cognition; Informatics; Cognitive architecture; Field (mathematics); Data science; Von Neumann architecture; Cognitive science; LIDA; Artificial intelligence; Human–computer interaction; Psychology","score_opus":0.014838213109259731,"score_gpt":0.318869128687606,"score_spread":0.3040309155783462,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2035931420","genre_codex":"other","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0026852882,0.22124995,0.06620116,0.1662889,0.006643921,0.000077112745,0.00019943723,0.00019922186,0.536455],"genre_scores_gemma":[0.4063426,0.32948536,0.072670385,0.056514252,0.043355938,0.0009799352,0.00035370848,0.000262665,0.09003513],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9969695,0.0013605737,0.00012120226,0.0004080528,0.0008852201,0.00025548835],"domain_scores_gemma":[0.996234,0.0023696683,0.00015704047,0.00030093154,0.00067593274,0.0002624241],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003373756,0.0014157662,0.001067828,0.003770386,0.0029540127,0.009990099,0.0022213145,0.0062413537,0.01248476],"category_scores_gemma":[0.004766388,0.00032225088,0.0009873201,0.0032028775,0.016923597,0.009486931,0.003149913,0.0085157305,0.00253866],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000022325903,0.00000437097,0.000017387738,0.000048451886,0.0000033025674,0.000022326127,0.00014584215,0.00010905419,0.000026377451,0.9904143,0.0046886876,0.0045177164],"study_design_scores_gemma":[0.000004260193,0.0000076697215,0.00006479787,0.00012027777,0.0000027385863,0.00007537824,0.00017695998,0.00039000393,0.000029353645,0.8931112,0.10601067,0.000006660838],"about_ca_topic_score_codex":0.0028599587,"about_ca_topic_score_gemma":0.0017264467,"teacher_disagreement_score":0.01248476,"about_ca_system_score_codex":0.005196924,"about_ca_system_score_gemma":0.0027904639,"threshold_uncertainty_score":0.04176569},"labels":[],"label_agreement":null},{"id":"W2036587865","doi":"10.4018/jssci.2010040106","title":"The Formal Design Model of a Real-Time Operating System (RTOS+)","year":2010,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Real-time operating system; Computer science; Process (computing); Embedded system; Set (abstract data type); Operating system; Programming language","score_opus":0.025345992987034816,"score_gpt":0.2861344496472068,"score_spread":0.260788456660172,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2036587865","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004816619,0.00039615383,0.984503,0.0005562489,0.00013854339,0.0001290374,0.00018241743,0.0005975273,0.008680517],"genre_scores_gemma":[0.2037407,0.0016153821,0.7798636,0.0007142721,0.00023427664,0.0010826031,0.000702967,0.00031107478,0.011735172],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9982693,0.00047534276,0.00022309845,0.00028761377,0.00058374007,0.00016081029],"domain_scores_gemma":[0.99807906,0.00081414223,0.00025456617,0.00039722346,0.0003704951,0.00008444066],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022436886,0.00078509975,0.0004401151,0.00059438474,0.0006709149,0.0027932553,0.0016154743,0.0013986815,0.0034045617],"category_scores_gemma":[0.0027603146,0.00065485475,0.0013239464,0.000481128,0.0030807515,0.003406884,0.0010822028,0.002401851,0.0012275577],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003175762,0.000029597235,0.00022126277,0.00025487502,0.000015494219,0.0001965373,0.00034162885,0.023191763,0.005292377,0.95251757,0.0018092023,0.016097886],"study_design_scores_gemma":[0.0001271754,0.0002810538,0.00037082564,0.00038643368,0.000089482826,0.0009053663,0.00022410286,0.17540075,0.017468022,0.47248226,0.33218718,0.000077363205],"about_ca_topic_score_codex":0.0025344326,"about_ca_topic_score_gemma":0.0015811876,"teacher_disagreement_score":0.0034045617,"about_ca_system_score_codex":0.0013474252,"about_ca_system_score_gemma":0.0029256984,"threshold_uncertainty_score":0.011865854},"labels":[],"label_agreement":null},{"id":"W2040512820","doi":"10.4018/jssci.2009010105","title":"On the System Algebra Foundations for Granular Computing","year":2009,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":92,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina; University of Calgary","funders":"","keywords":"Granular computing; Computer science; Theoretical computer science; Algebra over a field; Set (abstract data type); Representation (politics); Rough set; Artificial intelligence; Mathematics; Programming language; Pure mathematics","score_opus":0.02925712088019857,"score_gpt":0.30707537919863975,"score_spread":0.2778182583184412,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2040512820","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009732538,0.0041921884,0.9323455,0.0037792174,0.00036919236,0.000074280324,0.00023143516,0.00020056128,0.04907519],"genre_scores_gemma":[0.6261305,0.008192533,0.34592268,0.0019116617,0.0019224418,0.0004881564,0.00049851224,0.00020641397,0.014727115],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9978878,0.0006494775,0.00021162623,0.00029650945,0.000743013,0.00021156005],"domain_scores_gemma":[0.9967705,0.0017744806,0.0002863339,0.00047848988,0.00050752616,0.00018267754],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003450917,0.0007537126,0.0012831216,0.0022679274,0.0017502918,0.0045011565,0.0012394901,0.001554854,0.006351573],"category_scores_gemma":[0.0059128175,0.00055687415,0.0021609336,0.002148298,0.006520794,0.008404127,0.0029712983,0.004327428,0.0014204951],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000025942336,0.0000032178236,0.00002359401,0.000018542283,0.000003878328,0.000021935712,0.00005601453,0.0022199342,0.00011631201,0.99595463,0.00025376136,0.0013255617],"study_design_scores_gemma":[0.0000033695383,0.0000057313737,0.000030946598,0.0000127836,0.000002433623,0.000018890756,0.00001693833,0.010742826,0.00006720888,0.9858174,0.003274428,0.000006986568],"about_ca_topic_score_codex":0.0026850763,"about_ca_topic_score_gemma":0.001213837,"teacher_disagreement_score":0.006351573,"about_ca_system_score_codex":0.0024572439,"about_ca_system_score_gemma":0.0015679924,"threshold_uncertainty_score":0.021248102},"labels":[],"label_agreement":null},{"id":"W2045100658","doi":"10.4018/jssci.2011100105","title":"Intelligent Fault Recognition and Diagnosis for Rotating Machines using Neural Networks","year":2011,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Fault (geology); Artificial neural network; Field (mathematics); Noise (video); Set (abstract data type); Artificial intelligence; Condition monitoring; Machine learning; Performance indicator; Knowledge base; Medical diagnosis; Real-time computing; Engineering","score_opus":0.06274792368987836,"score_gpt":0.3273871241272278,"score_spread":0.26463920043734945,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045100658","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1649225,0.0012405361,0.82812005,0.0003530403,0.0000802049,0.00007385814,0.00007882661,0.0020488396,0.003082153],"genre_scores_gemma":[0.8884533,0.00035306622,0.10858176,0.00005530949,0.000024612724,0.00005992376,0.00012479874,0.000023319688,0.0023238857],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99979335,0.000047949376,0.00001907578,0.000053098614,0.000054383472,0.000032257147],"domain_scores_gemma":[0.9996228,0.00020917121,0.000053510383,0.000024246163,0.000081274324,0.00000890671],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041718336,0.00047891634,0.00033999895,0.0005288097,0.0002400988,0.0004792607,0.0004004526,0.0005474493,0.0010516704],"category_scores_gemma":[0.0016322084,0.00023927633,0.00036479675,0.00033150802,0.00024911517,0.0006059882,0.00023065292,0.00043495523,0.00028968652],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031668934,0.00013215104,0.0035556338,0.0001258495,0.00006309749,0.00014135762,0.00008965448,0.4895651,0.026111212,0.00243951,0.001184969,0.47627473],"study_design_scores_gemma":[0.000005247461,0.000026803213,0.0005334633,0.0000043002715,0.000005182648,0.000016187072,0.0000056749946,0.9962859,0.0023889008,0.00052212836,0.00020220409,0.000003965841],"about_ca_topic_score_codex":0.00844617,"about_ca_topic_score_gemma":0.0076740948,"teacher_disagreement_score":0.00844617,"about_ca_system_score_codex":0.0005915223,"about_ca_system_score_gemma":0.00039446805,"threshold_uncertainty_score":0.016793966},"labels":[],"label_agreement":null},{"id":"W2049723463","doi":"10.4018/jssci.2012010105","title":"The Formal Design Models of Digraph Architectures and Behaviors","year":2012,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Digraph; Theoretical computer science; Tree traversal; Graph; Model checking; Process (computing); Set (abstract data type); Architecture; Programming language; Discrete mathematics","score_opus":0.03336609099251815,"score_gpt":0.2999549490497843,"score_spread":0.2665888580572662,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2049723463","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0029959579,0.00030789958,0.9887875,0.0002586119,0.00005063706,0.00009805509,0.00017743142,0.0003480171,0.006976045],"genre_scores_gemma":[0.14156339,0.001966683,0.8417041,0.0004103266,0.00011466402,0.0011892697,0.00077034254,0.00025292992,0.01202833],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.998547,0.00041300332,0.00015899284,0.00030244712,0.00047098767,0.00010738989],"domain_scores_gemma":[0.9983908,0.00065406784,0.00018706439,0.00039813822,0.00031312398,0.00005680997],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014695962,0.0008416726,0.00037406618,0.0012965698,0.00092719507,0.0029480206,0.001716211,0.0011040221,0.004195507],"category_scores_gemma":[0.0033758904,0.0007945627,0.001380099,0.0011207499,0.002994006,0.003625635,0.0012635377,0.0024934025,0.0010160073],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006636965,0.000016444703,0.0001228453,0.0001070137,0.000011437033,0.00008570531,0.0001966722,0.0182727,0.0013257093,0.9683312,0.0005888971,0.010934751],"study_design_scores_gemma":[0.000032101143,0.00006127449,0.00016618198,0.0001507083,0.000056899906,0.00034579818,0.00014920256,0.14782333,0.004288932,0.7635298,0.083356224,0.000039631268],"about_ca_topic_score_codex":0.004050481,"about_ca_topic_score_gemma":0.0046447483,"teacher_disagreement_score":0.004195507,"about_ca_system_score_codex":0.0020802328,"about_ca_system_score_gemma":0.002566305,"threshold_uncertainty_score":0.015093207},"labels":[],"label_agreement":null},{"id":"W2049790740","doi":"10.4018/jssci.2009040101","title":"Exploring the Cognitive Foundations of Software Engineering","year":2009,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Social software engineering; Software engineering; Software requirements; Engineering informatics; Informatics; Software development; Software construction; Software; Data science; Programming language; Health informatics; Engineering","score_opus":0.06307701134867581,"score_gpt":0.30882449936883516,"score_spread":0.24574748802015933,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2049790740","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21310551,0.012679534,0.46462524,0.033297226,0.00019526707,0.000084731975,0.0001024058,0.00019659335,0.2757135],"genre_scores_gemma":[0.95880204,0.0024516564,0.03635207,0.00045164494,0.00010380555,0.00006831205,0.000040411494,0.0000147881065,0.0017152829],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99842876,0.0008609886,0.00006140543,0.00015489513,0.00038500578,0.00010884471],"domain_scores_gemma":[0.99146456,0.006987355,0.000398339,0.00042155702,0.0005415403,0.00018670764],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028641038,0.0003665628,0.00029522215,0.00228495,0.0012048222,0.0050414377,0.00067194126,0.0011425453,0.0016342603],"category_scores_gemma":[0.009368534,0.00028440298,0.00039594434,0.0012454547,0.013803236,0.006442319,0.0025364873,0.0019139253,0.00016297321],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000031459485,0.000011669827,0.00047128697,0.000033380307,0.000004961521,0.00003161035,0.0011435724,0.0013855031,0.00018131857,0.98833686,0.00018028366,0.008216432],"study_design_scores_gemma":[0.0000017241188,0.0000035092983,0.00031075304,0.000017372791,0.0000015190923,0.000018576797,0.00032527224,0.0029543946,0.00005288394,0.9942094,0.0021010998,0.0000034615534],"about_ca_topic_score_codex":0.0024925843,"about_ca_topic_score_gemma":0.0015464688,"teacher_disagreement_score":0.0050414377,"about_ca_system_score_codex":0.0022947348,"about_ca_system_score_gemma":0.0019167474,"threshold_uncertainty_score":0.016649544},"labels":[],"label_agreement":null},{"id":"W2056449002","doi":"10.4018/jssci.2009070107","title":"The Formal Design Model of a Telephone Switching System (TSS)","year":2009,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Process (computing); Software engineering; Formal specification; Formal methods; Process calculus; Programming language; Generator (circuit theory); Software deployment; Software system; Software; Power (physics)","score_opus":0.02792481716276665,"score_gpt":0.28366857818919805,"score_spread":0.2557437610264314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2056449002","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0050681145,0.00025580442,0.98296714,0.00072837505,0.00008322752,0.00010686136,0.00017796752,0.00045030916,0.010162174],"genre_scores_gemma":[0.221969,0.0011375508,0.75983113,0.00057984143,0.00016258805,0.0008916328,0.000798469,0.00020814854,0.014421675],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99866414,0.00038374157,0.00012994163,0.00020262066,0.00051313284,0.00010645067],"domain_scores_gemma":[0.9983967,0.0007726773,0.00017366854,0.00026420545,0.00034103746,0.00005172879],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017677364,0.0006891556,0.00032471435,0.00071976107,0.00068531954,0.0021939331,0.0013148222,0.0012986616,0.004232498],"category_scores_gemma":[0.002907273,0.00050986384,0.0010773881,0.0004954974,0.002871497,0.0030125552,0.0007595385,0.0019267492,0.0013013453],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023180535,0.000038335125,0.00021562369,0.0001734038,0.000013201801,0.00024257791,0.000413882,0.02438397,0.005266724,0.9527516,0.0016342357,0.014843206],"study_design_scores_gemma":[0.00010445085,0.0002095507,0.00034620278,0.000257825,0.000086940585,0.00087984075,0.0003725388,0.2044296,0.013600191,0.58809733,0.19153896,0.0000765542],"about_ca_topic_score_codex":0.003962624,"about_ca_topic_score_gemma":0.0025842881,"teacher_disagreement_score":0.004232498,"about_ca_system_score_codex":0.0017901465,"about_ca_system_score_gemma":0.0034994122,"threshold_uncertainty_score":0.014159083},"labels":[],"label_agreement":null},{"id":"W2056976301","doi":"10.4018/jssci.2009070101","title":"On Cognitive Computing","year":2009,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":196,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Cognitive computing; Computer science; Computational intelligence; Cognition; Cognitive architecture; Informatics; Cognitive science; Cognitive robotics; Artificial intelligence; Data science; Human–computer interaction; Embodied cognition; Psychology","score_opus":0.02009932085701511,"score_gpt":0.3189792059194498,"score_spread":0.2988798850624347,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2056976301","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0044205817,0.14444289,0.232055,0.053393457,0.0068773967,0.00022293965,0.0005394705,0.00070540485,0.5573429],"genre_scores_gemma":[0.4313896,0.18719962,0.16842008,0.035476383,0.022646898,0.0018804702,0.001387261,0.00056685536,0.15103287],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9973621,0.00093368837,0.00017923108,0.0004988124,0.00080641796,0.00021975352],"domain_scores_gemma":[0.9974107,0.0015085231,0.00011059886,0.00048079173,0.0003317259,0.00015764307],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021480424,0.001317198,0.0012825076,0.002338422,0.0021380282,0.008257134,0.0019153977,0.003964723,0.012731377],"category_scores_gemma":[0.0049186023,0.0004023546,0.0011738468,0.0025377243,0.010994277,0.010072708,0.004487639,0.004733572,0.0031295547],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005746908,0.00000608093,0.000050796032,0.00010891097,0.000011110412,0.00004376683,0.00019850899,0.00047159303,0.000071801114,0.97724336,0.007931365,0.013856986],"study_design_scores_gemma":[0.0000056026397,0.000007246152,0.00007019157,0.00010973166,0.0000050321364,0.00009409158,0.00007763899,0.00073812203,0.000056197237,0.903998,0.0948296,0.000008526791],"about_ca_topic_score_codex":0.0026282594,"about_ca_topic_score_gemma":0.0016771221,"teacher_disagreement_score":0.012731377,"about_ca_system_score_codex":0.003307307,"about_ca_system_score_gemma":0.0024257484,"threshold_uncertainty_score":0.042590678},"labels":[],"label_agreement":null},{"id":"W2062693824","doi":"10.4018/jssci.2009010102","title":"Hierarchies of Architectures of Collaborative Computational Intelligence","year":2009,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Computational intelligence; Cluster analysis; Reuse; Data science; Distributed knowledge; Knowledge management; Artificial intelligence","score_opus":0.014772091955967378,"score_gpt":0.30338579617603084,"score_spread":0.28861370422006344,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062693824","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.064697996,0.003745714,0.7196454,0.0049200123,0.00020634399,0.00031801907,0.0002839442,0.0011831893,0.20499936],"genre_scores_gemma":[0.70554715,0.0019007297,0.2708304,0.00041386508,0.00020629993,0.0004780706,0.0004415291,0.000116927644,0.02006494],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99684924,0.0013434445,0.00023433853,0.0004310766,0.00076703064,0.00037486316],"domain_scores_gemma":[0.99627244,0.0011578744,0.00023639169,0.001055009,0.0007304495,0.0005478887],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021987746,0.00044832908,0.00058786815,0.0016673465,0.0022296952,0.0050796946,0.0014865361,0.0015615196,0.007738277],"category_scores_gemma":[0.0059360815,0.00062711065,0.00073250686,0.0018275452,0.004290283,0.006286267,0.004344005,0.0016735586,0.0011814969],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014696954,0.000012821063,0.00028936626,0.000059174417,0.000014195481,0.000057273628,0.0005247459,0.0047225584,0.00033475453,0.983913,0.0013313349,0.008726163],"study_design_scores_gemma":[0.00002182965,0.00002007623,0.0003291051,0.000045453136,0.000015658827,0.000076730525,0.0002485159,0.027803164,0.00023799778,0.9472843,0.023900492,0.000016617436],"about_ca_topic_score_codex":0.0034612203,"about_ca_topic_score_gemma":0.004413452,"teacher_disagreement_score":0.007738277,"about_ca_system_score_codex":0.0025367083,"about_ca_system_score_gemma":0.0020726328,"threshold_uncertainty_score":0.025887072},"labels":[],"label_agreement":null},{"id":"W2063832198","doi":"10.4018/ijssci.2013070104","title":"Formal Models and Cognitive Mechanisms of the Human Sensory System","year":2013,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Sensory system; Computer science; Perception; Cognition; Set (abstract data type); Neuroscience; Cognitive systems; Cognitive model; Human–computer interaction; Cognitive science; Artificial intelligence; Psychology","score_opus":0.028791307960404564,"score_gpt":0.2839212865503647,"score_spread":0.2551299785899601,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2063832198","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.037612736,0.0039053122,0.8799809,0.0043378514,0.00014251046,0.0001274484,0.00049785885,0.0004956895,0.07289966],"genre_scores_gemma":[0.81487584,0.0030283048,0.16743411,0.0005642421,0.0002523526,0.0004940885,0.0004477856,0.00007267775,0.012830636],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991648,0.00032858877,0.00005895611,0.00011234874,0.00023908853,0.00009622114],"domain_scores_gemma":[0.99869615,0.00073913485,0.00014369212,0.00018106861,0.00016668467,0.00007328465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014072049,0.0006969237,0.00036293903,0.0009513035,0.000733856,0.0029314207,0.001566119,0.0011511939,0.0036470022],"category_scores_gemma":[0.0025013182,0.00032608863,0.00093239744,0.0005998174,0.005073652,0.00329192,0.001186367,0.0012063897,0.0005163365],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005073353,0.0000063745742,0.000042727803,0.000028644974,0.000004704132,0.0000317626,0.00015878696,0.0074004917,0.00023592587,0.99025047,0.0002711639,0.0015638373],"study_design_scores_gemma":[0.000017113209,0.00001436491,0.00007180826,0.00003631923,0.000008682566,0.00005179549,0.00010034193,0.029086402,0.0002026839,0.96332866,0.007072006,0.000009928234],"about_ca_topic_score_codex":0.003504759,"about_ca_topic_score_gemma":0.0022386527,"teacher_disagreement_score":0.0036470022,"about_ca_system_score_codex":0.001611233,"about_ca_system_score_gemma":0.0014336441,"threshold_uncertainty_score":0.012200415},"labels":[],"label_agreement":null},{"id":"W2066333020","doi":"10.4018/ijssci.2011070106","title":"The Formal Design Models of a Universal Array (UA) and its Implementation","year":2011,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Compiler; Pointer (user interface); Programming language; Code generation; Process calculus; Process (computing); Theoretical computer science; Key (lock); Artificial intelligence; Operating system","score_opus":0.06772236574591192,"score_gpt":0.3095873111627846,"score_spread":0.24186494541687267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2066333020","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0030861555,0.00021563204,0.9923849,0.00019404228,0.00003580604,0.00006098705,0.000078718884,0.00031372363,0.0036300877],"genre_scores_gemma":[0.12634556,0.0010031576,0.86618954,0.00025025423,0.00010413521,0.000691729,0.00031463717,0.00029203726,0.0048089703],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99689,0.0008150477,0.0004164639,0.0005443374,0.001092424,0.00024178112],"domain_scores_gemma":[0.9961361,0.001465796,0.0004755624,0.0011036582,0.00071392447,0.000104872626],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030385864,0.00075664476,0.0005816111,0.0009901333,0.0011025707,0.004020694,0.0021683634,0.0013478615,0.0034312506],"category_scores_gemma":[0.0058060596,0.00087669695,0.0018111048,0.0010523555,0.0046405485,0.006949048,0.0016761945,0.0028453292,0.0010923991],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012643323,0.000016960881,0.00019062094,0.00012768245,0.000011742768,0.00006715456,0.00034127908,0.009739722,0.0025330854,0.9731224,0.0005286825,0.01330804],"study_design_scores_gemma":[0.00003705607,0.00015365571,0.00025137496,0.00023583526,0.000096122654,0.0006180042,0.0003184733,0.12997487,0.017098676,0.7328167,0.11832495,0.00007427357],"about_ca_topic_score_codex":0.0018414749,"about_ca_topic_score_gemma":0.001362459,"teacher_disagreement_score":0.004020694,"about_ca_system_score_codex":0.001664307,"about_ca_system_score_gemma":0.0027212687,"threshold_uncertainty_score":0.01606977},"labels":[],"label_agreement":null},{"id":"W2069855588","doi":"10.4018/jssci.2010070103","title":"Role-Based Autonomic Systems","year":2010,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Service-Oriented Architecture and Web Services","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nipissing University","funders":"","keywords":"Autonomic computing; Computer science; Abnormality; Order (exchange); Human–computer interaction; Distributed computing; Computer security; Cloud computing; Operating system","score_opus":0.008221254205279879,"score_gpt":0.2607790423941376,"score_spread":0.2525577881888577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2069855588","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02929364,0.0074509094,0.7792308,0.0036606542,0.0015187581,0.0005445811,0.00027509892,0.0024922779,0.17553325],"genre_scores_gemma":[0.74245393,0.0041650506,0.21971008,0.00094193325,0.00075940625,0.00059426023,0.00037527914,0.00013533299,0.030864742],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99872285,0.00039005335,0.0001090189,0.00024093525,0.00038364445,0.00015348055],"domain_scores_gemma":[0.99877876,0.00031046724,0.00015604605,0.0002630164,0.00028352765,0.0002081407],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015101604,0.00049876305,0.00059532706,0.00049343845,0.001387596,0.0030642687,0.001824249,0.0011773619,0.0044945274],"category_scores_gemma":[0.002901473,0.00033844955,0.00046898323,0.000560632,0.0013439858,0.0026579546,0.002069042,0.001176983,0.001747627],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011620755,0.00011106054,0.0009731629,0.0002188849,0.00006267326,0.00045813702,0.0006376101,0.025211923,0.005715296,0.87608063,0.010661823,0.07975259],"study_design_scores_gemma":[0.00017436322,0.00020618712,0.0008280803,0.0001687654,0.000096458316,0.0009987121,0.0003710349,0.21846867,0.004199041,0.47932154,0.2950781,0.000089111236],"about_ca_topic_score_codex":0.0010692719,"about_ca_topic_score_gemma":0.0010069074,"teacher_disagreement_score":0.0044945274,"about_ca_system_score_codex":0.00069128023,"about_ca_system_score_gemma":0.0009858721,"threshold_uncertainty_score":0.015035689},"labels":[],"label_agreement":null},{"id":"W2070016297","doi":"10.4018/ijssci.2011070103","title":"Empirical Studies on the Functional Complexity of Software in Large-Scale Software Systems","year":2011,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Software construction; Software metric; Software system; Software sizing; Programming complexity; Software development; Software; Software analytics; Software engineering; Theoretical computer science; Programming language","score_opus":0.1654289918631549,"score_gpt":0.3517204265598767,"score_spread":0.18629143469672177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2070016297","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99001783,0.000210999,0.0076737483,0.00014323642,0.00000296681,0.00002815392,0.00007793001,0.000009098876,0.0018360905],"genre_scores_gemma":[0.99802244,0.000110210975,0.0016067128,0.000014150147,0.0000072461316,0.00002632571,0.00012015472,0.000004911271,0.00008777395],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99502337,0.0018747371,0.00035805107,0.0005137387,0.0020289095,0.0002012037],"domain_scores_gemma":[0.724534,0.23062105,0.025354726,0.007823902,0.010001065,0.0016653347],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004966176,0.00033112994,0.00028982438,0.0027299384,0.00078189524,0.0010465547,0.0007278915,0.00046462117,0.0014109637],"category_scores_gemma":[0.10677824,0.0002114722,0.00031532385,0.0034987608,0.002865451,0.0034611302,0.0011618537,0.0010548512,0.00011859816],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018412647,0.0007518333,0.87356764,0.0004128464,0.00028217878,0.00033495663,0.008102578,0.024594454,0.0026661698,0.026229335,0.00092121825,0.061952688],"study_design_scores_gemma":[0.00002333419,0.00045213636,0.9320896,0.00011684109,0.000063821855,0.0005092787,0.005525448,0.036541622,0.0020541563,0.019745972,0.002827563,0.000050272673],"about_ca_topic_score_codex":0.0018895216,"about_ca_topic_score_gemma":0.0024977669,"teacher_disagreement_score":0.004966176,"about_ca_system_score_codex":0.0008995986,"about_ca_system_score_gemma":0.0005417451,"threshold_uncertainty_score":0.026263952},"labels":[],"label_agreement":null},{"id":"W2070141931","doi":"10.4018/jssci.2011010104","title":"On Cognitive Models of Causal Inferences and Causation Networks","year":2011,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Causation; Causal inference; Computer science; Causality (physics); Cognition; Inference; Causal reasoning; Cognitive computing; Artificial intelligence; Cognitive science; Causal model; Set (abstract data type); Perception; Causal structure; Cognitive psychology; Data science; Psychology; Epistemology; Mathematics; Econometrics","score_opus":0.05421120689825,"score_gpt":0.2994252472643807,"score_spread":0.2452140403661307,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2070141931","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008963345,0.002374502,0.95004547,0.006078428,0.00013781324,0.00006977485,0.0003594499,0.00020341776,0.031767823],"genre_scores_gemma":[0.5697185,0.006829273,0.4095022,0.0015537862,0.0007057504,0.00069041166,0.00097151793,0.00014916382,0.009879405],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9957402,0.002272568,0.00024215676,0.00066121406,0.00086658745,0.00021724582],"domain_scores_gemma":[0.9811989,0.014800929,0.0012680162,0.0011599332,0.0012077742,0.00036435673],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0057107573,0.001440626,0.0010196281,0.0045792297,0.001971341,0.0057301214,0.002636344,0.0025972384,0.0068953503],"category_scores_gemma":[0.019622386,0.00077747606,0.0019505481,0.0035138684,0.0070998734,0.013805048,0.0027283148,0.003437919,0.00095416966],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008406358,0.000008461098,0.00014194973,0.000042671025,0.00001879344,0.00003776879,0.0001903857,0.009978842,0.000051999537,0.985033,0.00044809928,0.0040395237],"study_design_scores_gemma":[0.000004258507,0.0000036036095,0.000041287047,0.000017342567,0.0000073894666,0.000024165,0.000025539008,0.015447079,0.000026848655,0.9825179,0.0018794539,0.0000051541697],"about_ca_topic_score_codex":0.0050246767,"about_ca_topic_score_gemma":0.003864529,"teacher_disagreement_score":0.0068953503,"about_ca_system_score_codex":0.0029641108,"about_ca_system_score_gemma":0.0018123446,"threshold_uncertainty_score":0.030201674},"labels":[],"label_agreement":null},{"id":"W2076767174","doi":"10.4018/jssci.2012070105","title":"Evaluating the Security Level of a Cryptosystem based on Chaos","year":2012,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cellular Automata and Applications","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Cryptosystem; Computer science; Chaotic; Surrogate data; Attractor; Hybrid cryptosystem; Dimension (graph theory); Theoretical computer science; CHAOS (operating system); Paillier cryptosystem; Algorithm; Cryptography; Mathematics; Artificial intelligence; Computer security; Nonlinear system","score_opus":0.1398345414593873,"score_gpt":0.3974886792284687,"score_spread":0.2576541377690814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2076767174","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8658842,0.00033544557,0.12988116,0.00012001997,0.000073349394,0.00009313042,0.00012867621,0.00029042023,0.003193526],"genre_scores_gemma":[0.9870165,0.00007159874,0.012591643,0.0000069587104,0.0000060008206,0.000020022337,0.000056381017,0.000013996745,0.00021681013],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99827504,0.00042802212,0.00014047997,0.0001913653,0.00081608206,0.00014899609],"domain_scores_gemma":[0.9913818,0.005473408,0.00094092236,0.0009995064,0.00093513937,0.00026918517],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014523136,0.0005040656,0.00053684047,0.0012244442,0.0004576201,0.0007631014,0.00040299393,0.00074006466,0.001216833],"category_scores_gemma":[0.011418931,0.00013821626,0.00031159402,0.00041644147,0.0011382223,0.0016952858,0.00076475093,0.0005354931,0.00021441844],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027573344,0.0004884714,0.035723988,0.00079601386,0.00032547218,0.0007390654,0.0005123963,0.1328138,0.6492427,0.03781004,0.0006693629,0.1381214],"study_design_scores_gemma":[0.00007390163,0.004378895,0.01497889,0.00007812509,0.00009161927,0.0009643202,0.00020182352,0.36924532,0.59819937,0.009613484,0.0020499465,0.00012435399],"about_ca_topic_score_codex":0.00021227644,"about_ca_topic_score_gemma":0.00015380273,"teacher_disagreement_score":0.0014523136,"about_ca_system_score_codex":0.0005693424,"about_ca_system_score_gemma":0.00033753423,"threshold_uncertainty_score":0.0076806545},"labels":[],"label_agreement":null},{"id":"W2078392793","doi":"10.4018/jssci.2009040104","title":"A Theory of Program Comprehension","year":2009,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Software Engineering Research","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal","funders":"","keywords":"Comprehension; Program comprehension; Computer science; Software; Process (computing); Vision science; Perspective (graphical); Cognitive science; Human–computer interaction; Artificial intelligence; Software system; Programming language; Psychology","score_opus":0.029852218194042573,"score_gpt":0.3386157124770408,"score_spread":0.3087634942829982,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078392793","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00961431,0.0033236465,0.83354205,0.010754243,0.0003371466,0.00027449717,0.0005993694,0.0014453084,0.14010943],"genre_scores_gemma":[0.5601639,0.0052124225,0.3770687,0.006238263,0.0014711445,0.0016292651,0.0022830046,0.0011160823,0.044817124],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.995911,0.001748268,0.00026654088,0.00087597163,0.00086776336,0.00033047615],"domain_scores_gemma":[0.98933136,0.007644726,0.00045194494,0.0010164817,0.0013179438,0.00023758365],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004125737,0.0012610807,0.00083818944,0.0027851625,0.0021858248,0.005075065,0.0024586455,0.003490826,0.017695216],"category_scores_gemma":[0.015498008,0.00073179865,0.002800019,0.001915621,0.010041949,0.01821342,0.0032132755,0.0048551937,0.0036129255],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015383881,0.000026188487,0.00021238292,0.00015574391,0.000014359649,0.00007068788,0.0013821069,0.0011790221,0.00029480658,0.9764712,0.0032601722,0.016918084],"study_design_scores_gemma":[0.000018698345,0.00002168984,0.00015172905,0.000079123085,0.000014226199,0.00009568253,0.00019522251,0.0048871306,0.000361437,0.96999145,0.024171414,0.000012291394],"about_ca_topic_score_codex":0.0030982252,"about_ca_topic_score_gemma":0.0013127876,"teacher_disagreement_score":0.017695216,"about_ca_system_score_codex":0.0028443525,"about_ca_system_score_gemma":0.0026830123,"threshold_uncertainty_score":0.059196413},"labels":[],"label_agreement":null},{"id":"W2084294763","doi":"10.4018/ijssci.2014010103","title":"Simulation and Visualization of Concept Algebra in MATLAB","year":2014,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Visualization; MATLAB; Algebra over a field; Programming language; Visual modeling; Software; Theoretical computer science; Artificial intelligence; Unified Modeling Language; Mathematics; Pure mathematics","score_opus":0.02196468163088614,"score_gpt":0.3258940713820529,"score_spread":0.30392938975116673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2084294763","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.046685193,0.00007708818,0.9298302,0.00036921643,0.000065773915,0.000099044475,0.00039130397,0.007974189,0.014508062],"genre_scores_gemma":[0.53901225,0.0002588359,0.45352903,0.0001225637,0.000022612881,0.00044932033,0.0005280778,0.0007278455,0.005349456],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99942064,0.00023457047,0.00004676137,0.0000687589,0.00018920143,0.000040093055],"domain_scores_gemma":[0.9983059,0.0011580555,0.000094749084,0.00018524838,0.000201284,0.00005477985],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008550916,0.00040502977,0.00030778826,0.0004813514,0.00026937385,0.0012178388,0.00092557975,0.00064340595,0.009194202],"category_scores_gemma":[0.0044516753,0.00022867558,0.0005378833,0.00032082913,0.00085035374,0.001253239,0.0012631912,0.0006702304,0.00088147505],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007409001,0.00013922688,0.0033166988,0.0004089706,0.000067122484,0.00082812324,0.002183867,0.4924895,0.032308906,0.37795547,0.0061969855,0.083364256],"study_design_scores_gemma":[0.0001196945,0.000092884504,0.00039161928,0.00007288204,0.000016588727,0.00022331059,0.000112303576,0.8925226,0.023933513,0.052571353,0.02991021,0.00003308685],"about_ca_topic_score_codex":0.0012106715,"about_ca_topic_score_gemma":0.0008560895,"teacher_disagreement_score":0.009194202,"about_ca_system_score_codex":0.00050270074,"about_ca_system_score_gemma":0.00079841906,"threshold_uncertainty_score":0.030757666},"labels":[],"label_agreement":null},{"id":"W2085152848","doi":"10.4018/jssci.2011100101","title":"A Formal Knowledge Representation System (FKRS) for the Intelligent Knowledge Base of a Cognitive Learning Engine","year":2011,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Knowledge representation and reasoning; Knowledge base; Representation (politics); Knowledge-based systems; Process (computing); Open Knowledge Base Connectivity; Procedural knowledge; Artificial intelligence; Component (thermodynamics); Relation (database); Object (grammar); Cognitive model; Cognition; Knowledge acquisition; Programming language; Knowledge management; Personal knowledge management; Organizational learning","score_opus":0.06104816726580508,"score_gpt":0.33031034783020186,"score_spread":0.26926218056439677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2085152848","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0025908605,0.0001691077,0.9834464,0.00050970085,0.0001039515,0.00018265295,0.0002727846,0.0070808735,0.0056435885],"genre_scores_gemma":[0.065299734,0.00036072923,0.9259958,0.00033157162,0.000091321264,0.00035803928,0.0012104542,0.0003614369,0.0059909574],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978036,0.0005998073,0.00036453118,0.00048029405,0.00060028513,0.00015131252],"domain_scores_gemma":[0.9975405,0.000914592,0.00024715907,0.0006926706,0.00047201224,0.00013317386],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034944937,0.00065222074,0.0007174309,0.0018512777,0.0010230293,0.004576846,0.0027559053,0.0017285568,0.008129537],"category_scores_gemma":[0.005783067,0.0005475753,0.001791426,0.0010253111,0.00231492,0.006396119,0.0018406922,0.0024520608,0.0033966787],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010921523,0.00014891282,0.0005322453,0.00047318995,0.00007764338,0.0005122219,0.0009926739,0.024287613,0.011674292,0.8218127,0.012018403,0.12736093],"study_design_scores_gemma":[0.0001669377,0.00020994323,0.0005398413,0.00043160786,0.0002148967,0.0010139735,0.00027295438,0.2971313,0.021969449,0.37424028,0.30361322,0.00019554236],"about_ca_topic_score_codex":0.00499234,"about_ca_topic_score_gemma":0.0033102983,"teacher_disagreement_score":0.008129537,"about_ca_system_score_codex":0.0018023683,"about_ca_system_score_gemma":0.004334572,"threshold_uncertainty_score":0.02719599},"labels":[],"label_agreement":null},{"id":"W2088048929","doi":"10.4018/jssci.2011010107","title":"The Formal Design Model of a File Management System (FMS)","year":2011,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; File system; Component (thermodynamics); Software; Operating system; Software engineering","score_opus":0.05376836211951563,"score_gpt":0.2717951091119203,"score_spread":0.21802674699240465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2088048929","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0055715023,0.00035780325,0.98237556,0.00067064766,0.00006935142,0.00020578563,0.0002435359,0.00045791018,0.010047922],"genre_scores_gemma":[0.18785635,0.0010999616,0.7966053,0.00046436372,0.00015108305,0.0013336154,0.00064873847,0.00016835751,0.011672211],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985814,0.00037425145,0.00015651804,0.0002853412,0.0004768969,0.00012560264],"domain_scores_gemma":[0.9986992,0.000509242,0.00019585472,0.00027035686,0.00025845895,0.00006692912],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017954934,0.0007490291,0.00035794458,0.0008399732,0.0009970741,0.0028538802,0.0018912995,0.0017770072,0.0035409688],"category_scores_gemma":[0.002506945,0.00064197904,0.0011286708,0.00082934456,0.0033930598,0.0036877969,0.0011808161,0.0019731657,0.0011666935],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026336904,0.000035306755,0.00033262323,0.00021531447,0.000013279145,0.00030322393,0.0005301964,0.015721181,0.004293436,0.9617099,0.0015282206,0.015290904],"study_design_scores_gemma":[0.0001060721,0.00029890635,0.00059978745,0.0003778242,0.000096387346,0.0013949744,0.00041071337,0.16970679,0.012380717,0.55059993,0.26394448,0.00008346054],"about_ca_topic_score_codex":0.0032848467,"about_ca_topic_score_gemma":0.0023356215,"teacher_disagreement_score":0.0035409688,"about_ca_system_score_codex":0.0016511572,"about_ca_system_score_gemma":0.0031612585,"threshold_uncertainty_score":0.011979997},"labels":[],"label_agreement":null},{"id":"W2089640190","doi":"10.4018/jssci.2009040103","title":"On the Cognitive Complexity of Software and its Quantification and Formal Measurement","year":2009,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Programming complexity; Software construction; Software engineering; Cognitive complexity; Software sizing; Software system; Software; Software development; Verification and validation; Software metric; Theoretical computer science; Programming language; Cognition; Mathematics; Statistics","score_opus":0.0955717602813108,"score_gpt":0.3229634957548701,"score_spread":0.2273917354735593,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2089640190","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19677465,0.0018971643,0.750812,0.0037689554,0.00008423719,0.00014693972,0.00017652503,0.00017691805,0.04616261],"genre_scores_gemma":[0.9224308,0.0006778444,0.07556418,0.00024152808,0.000075910226,0.0003260146,0.00009858651,0.00003359391,0.00055160513],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98943186,0.0048596705,0.00065554667,0.0011689165,0.003482502,0.00040153062],"domain_scores_gemma":[0.9231164,0.06134847,0.0051691937,0.006281304,0.0033486902,0.000735964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009184771,0.00091715745,0.0006138132,0.004853556,0.0013551326,0.004680234,0.0011975738,0.0012516755,0.0019486368],"category_scores_gemma":[0.06225382,0.00046466745,0.0010182224,0.0024228054,0.018924318,0.010823834,0.0032999718,0.0024208953,0.00016180109],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029779878,0.00004206747,0.0025439307,0.00011287466,0.000019827157,0.000029398958,0.0015184153,0.0051832674,0.0013508691,0.9714884,0.00018565745,0.017495563],"study_design_scores_gemma":[0.00000846321,0.000058609054,0.0038724756,0.00007654997,0.00001293218,0.000069260095,0.00044148494,0.013973217,0.0008509544,0.9792078,0.0013923327,0.000035951034],"about_ca_topic_score_codex":0.0027528193,"about_ca_topic_score_gemma":0.0011762711,"teacher_disagreement_score":0.009184771,"about_ca_system_score_codex":0.003526693,"about_ca_system_score_gemma":0.001760587,"threshold_uncertainty_score":0.04857433},"labels":[],"label_agreement":null},{"id":"W2089688185","doi":"10.4018/jssci.2009010106","title":"Adaptive Computation Paradigm in Knowledge Representation","year":2009,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Artificial intelligence; Representation (politics); Computational intelligence; Data science; Paradigm shift; Software; Computation; Robotics; Theoretical computer science; Human–computer interaction; Machine learning; Robot","score_opus":0.0403382098157384,"score_gpt":0.34767737687076716,"score_spread":0.3073391670550288,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2089688185","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0059241597,0.009542107,0.9172256,0.005406152,0.00047921255,0.00012648334,0.00013995824,0.00026389994,0.06089231],"genre_scores_gemma":[0.46746844,0.019486872,0.47896942,0.0024422964,0.0016608445,0.0010738047,0.00047753856,0.000109302884,0.02831147],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99885106,0.00032850564,0.00007985512,0.0002761295,0.00039141963,0.00007300776],"domain_scores_gemma":[0.9992387,0.00040731914,0.00005353713,0.00013750988,0.00012070579,0.000042283475],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010233251,0.00054299954,0.0007150113,0.0010651224,0.00058085134,0.003706089,0.0017250683,0.0017418475,0.0036511526],"category_scores_gemma":[0.0028666174,0.00023211226,0.0008385565,0.0018901889,0.003233145,0.004712705,0.0017410143,0.0023319786,0.0008877884],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015168083,0.000011540062,0.00009429442,0.00011259118,0.000023158758,0.000074064366,0.00018779779,0.009834981,0.00075523526,0.9560724,0.002154322,0.030664401],"study_design_scores_gemma":[0.000012001775,0.000020020754,0.00008441586,0.000037934282,0.000014381816,0.00010204681,0.000066027955,0.05951479,0.0003901251,0.9203403,0.019406203,0.000011858375],"about_ca_topic_score_codex":0.0017988741,"about_ca_topic_score_gemma":0.0011236024,"teacher_disagreement_score":0.003706089,"about_ca_system_score_codex":0.0014233929,"about_ca_system_score_gemma":0.0010534016,"threshold_uncertainty_score":0.012214303},"labels":[],"label_agreement":null},{"id":"W2128847842","doi":"10.4018/jssci.2009010101","title":"On Abstract Intelligence","year":2009,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":181,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Human intelligence; Artificial intelligence; Artificial intelligence, situated approach; Marketing and artificial intelligence; Artificial general intelligence; Abstraction; Intelligent decision support system; Cognitive science; Psychology; Epistemology","score_opus":0.023871445261865736,"score_gpt":0.31641211075212256,"score_spread":0.2925406654902568,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128847842","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010043943,0.036050558,0.11543936,0.044180848,0.003150431,0.0001184129,0.000512523,0.00032455917,0.79017943],"genre_scores_gemma":[0.7407065,0.04093615,0.056869704,0.021680858,0.008588215,0.0006746746,0.0012632284,0.0003969829,0.1288837],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9962804,0.0013762013,0.0002667903,0.0007546256,0.0010154346,0.00030659564],"domain_scores_gemma":[0.9967698,0.001392178,0.0002167402,0.0007984639,0.00064565474,0.00017721648],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031098418,0.0009130643,0.0008622081,0.0024176696,0.0025327755,0.007945993,0.0013021928,0.003077009,0.012352994],"category_scores_gemma":[0.008370521,0.00035499787,0.00093961484,0.0019209088,0.01667166,0.014179737,0.0047623613,0.0049089333,0.003128512],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000026901525,0.0000025721665,0.000047127927,0.000020868443,0.0000023221726,0.00001124621,0.00013994833,0.00012327921,0.0000220129,0.99240714,0.0035216394,0.0036992093],"study_design_scores_gemma":[0.000002887574,0.0000042324823,0.000053123258,0.000041420164,0.0000019942406,0.00003357296,0.000071468115,0.0002604145,0.000041813317,0.95233285,0.047152795,0.000003471787],"about_ca_topic_score_codex":0.0022053942,"about_ca_topic_score_gemma":0.0011412111,"teacher_disagreement_score":0.012352994,"about_ca_system_score_codex":0.003857822,"about_ca_system_score_gemma":0.0019897353,"threshold_uncertainty_score":0.041324914},"labels":[],"label_agreement":null},{"id":"W2176546791","doi":"10.4018/jssci.2010100102","title":"Granular Computing and Human-Centricity in Computational Intelligence","year":2010,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Granular computing; Computer science; Fuzzy logic; Fuzzy set; Facet (psychology); Cluster analysis; Computational intelligence; Set (abstract data type); Rough set; Suite; Artificial intelligence; Theoretical computer science; Data mining; Data science","score_opus":0.02090298652578876,"score_gpt":0.3155572588227323,"score_spread":0.2946542722969435,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2176546791","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.032437444,0.026634663,0.8719325,0.011974433,0.00065924705,0.00014031395,0.00013553961,0.00035795584,0.055727903],"genre_scores_gemma":[0.72858083,0.011151011,0.2520491,0.0008353853,0.0008451216,0.00023808931,0.00009364864,0.000060183647,0.006146611],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9977629,0.0010418206,0.00016048916,0.00028163553,0.00060911133,0.00014402918],"domain_scores_gemma":[0.995458,0.0034004922,0.00023719641,0.00055444107,0.00022077195,0.00012912217],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030936308,0.00052220863,0.00101853,0.0019109607,0.0008774808,0.0067348545,0.0009063861,0.0014745453,0.0013592857],"category_scores_gemma":[0.006712928,0.0003662783,0.00076222455,0.0024712684,0.00822683,0.0051676035,0.0018036582,0.0020576017,0.00019101887],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020223195,0.000010700463,0.00021971394,0.000092142334,0.00002101454,0.00005991923,0.00027212416,0.009672472,0.00030686325,0.973961,0.0008318756,0.014531992],"study_design_scores_gemma":[0.000008063882,0.000016007834,0.0002375156,0.000041333937,0.000009463928,0.000040398158,0.00012901289,0.018181337,0.0002314847,0.97461265,0.006479892,0.000012787523],"about_ca_topic_score_codex":0.0011755241,"about_ca_topic_score_gemma":0.0011192742,"teacher_disagreement_score":0.0067348545,"about_ca_system_score_codex":0.0024410703,"about_ca_system_score_gemma":0.00090803666,"threshold_uncertainty_score":0.017711222},"labels":[],"label_agreement":null},{"id":"W2179756850","doi":"10.4018/ijssci.2015010101","title":"Feature and Rank Level Fusion for Privacy Preserved Multi-Biometric System","year":2015,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Biometrics; Random projection; Feature (linguistics); Authentication (law); Artificial intelligence; Face (sociological concept); Projection (relational algebra); Pattern recognition (psychology); Facial recognition system; Template; Data mining; Computer security; Algorithm","score_opus":0.12280318711744213,"score_gpt":0.3503421812595449,"score_spread":0.22753899414210277,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2179756850","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.036929533,0.00044408775,0.9599101,0.00021569568,0.000071895854,0.000045753946,0.00010518295,0.000577784,0.0017000269],"genre_scores_gemma":[0.7605194,0.00034316527,0.23409832,0.00015125552,0.00009719881,0.00006594562,0.00027234643,0.00004973045,0.004402633],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99821234,0.00029247734,0.00010732902,0.00038278374,0.0008299018,0.00017519102],"domain_scores_gemma":[0.9994566,0.000075837794,0.000079336016,0.00014533894,0.00020529039,0.000037617552],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00097554375,0.00058250705,0.00092184235,0.00060783804,0.0005701366,0.0013239079,0.0007892659,0.0009056114,0.0028727017],"category_scores_gemma":[0.0015646226,0.00023969372,0.0010498661,0.00069498434,0.0004379479,0.001587142,0.0012220035,0.0008215236,0.0010095865],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009464668,0.00026812888,0.002253681,0.0002499186,0.00021556219,0.00034131945,0.00021695677,0.1059949,0.17485483,0.01785894,0.0035765811,0.69322276],"study_design_scores_gemma":[0.00003463677,0.00055966206,0.0031322967,0.000018807386,0.00009527126,0.00053401495,0.0000677426,0.9074755,0.075204104,0.0085430015,0.0042489823,0.00008606812],"about_ca_topic_score_codex":0.0010533831,"about_ca_topic_score_gemma":0.00093463,"teacher_disagreement_score":0.0028727017,"about_ca_system_score_codex":0.00053628127,"about_ca_system_score_gemma":0.0005680318,"threshold_uncertainty_score":0.009610176},"labels":[],"label_agreement":null},{"id":"W2180731253","doi":"10.4018/ijssci.2015010103","title":"On the Incremental Union of Relations","year":2015,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Brain Institute","funders":"","keywords":"Property (philosophy); Relation (database); Computer science; Algebraic number; Algebra over a field; Set (abstract data type); Semantics (computer science); Theoretical computer science; Relational algebra; Mathematics; Programming language; Epistemology; Pure mathematics; Relational database","score_opus":0.04365680380672819,"score_gpt":0.3088293026768944,"score_spread":0.2651724988701662,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2180731253","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.076923445,0.0017402429,0.84435034,0.001661129,0.00041149574,0.000113188864,0.00028180217,0.0006348596,0.07388348],"genre_scores_gemma":[0.7035524,0.0019504772,0.2745772,0.0006616745,0.00069988536,0.0002275897,0.0004989059,0.00032124965,0.017510656],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9962469,0.0009268491,0.0002715113,0.0010074963,0.0012091596,0.000338203],"domain_scores_gemma":[0.99516076,0.0020777632,0.00041776532,0.0010776779,0.0009752593,0.00029076962],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033117314,0.0005022819,0.0006425223,0.0024233437,0.002182918,0.003682086,0.0016686352,0.0008966099,0.0048817215],"category_scores_gemma":[0.009038904,0.00045184698,0.001149369,0.0018812213,0.007889555,0.015027694,0.0050040716,0.0024779083,0.00089766044],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022697128,0.000007162608,0.000096598254,0.000020705702,0.0000043457253,0.000057097208,0.0002442877,0.0009627246,0.00055198517,0.98946583,0.0004103764,0.008156193],"study_design_scores_gemma":[0.000012870582,0.000026822296,0.00014566747,0.000018740415,0.000016620736,0.00017439135,0.000110440575,0.010497099,0.0010596936,0.9722944,0.015625276,0.000017942599],"about_ca_topic_score_codex":0.0023137543,"about_ca_topic_score_gemma":0.0014504968,"teacher_disagreement_score":0.0048817215,"about_ca_system_score_codex":0.0015396037,"about_ca_system_score_gemma":0.0011086705,"threshold_uncertainty_score":0.017514348},"labels":[],"label_agreement":null},{"id":"W2201096852","doi":"10.4018/ijssci.2015040103","title":"Cognitive Informatics and Computational Intelligence","year":2015,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; University of New Brunswick; University of Calgary","funders":"","keywords":"Cognitive computing; Computer science; Informatics; Cognition; LIDA; Multidisciplinary approach; Computational intelligence; Data science; Cognitive science; Field (mathematics); Information science; Engineering informatics; Artificial intelligence; Health informatics; Cognitive model; Psychology; Sociology; Social science; Library science; Engineering","score_opus":0.044278973863909395,"score_gpt":0.3268779665015775,"score_spread":0.28259899263766813,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2201096852","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014317941,0.19153547,0.11967511,0.08065557,0.0026736753,0.00015702122,0.0005065184,0.00047529393,0.5900034],"genre_scores_gemma":[0.73805,0.11124481,0.07581911,0.018842015,0.008451509,0.0006967988,0.00070428196,0.00023089399,0.045960564],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99674207,0.0013209125,0.00017805978,0.0006619302,0.0008494239,0.00024750567],"domain_scores_gemma":[0.9962165,0.0025447572,0.0002126646,0.00051289453,0.0003195392,0.00019363627],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026451012,0.0009359738,0.0010515207,0.0033464788,0.0018104436,0.009286346,0.0010389864,0.0025750631,0.0064374227],"category_scores_gemma":[0.0051642023,0.00029444887,0.00068383565,0.003008532,0.020525297,0.007922437,0.0032907422,0.0042855702,0.0012712841],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003609083,0.000004500667,0.00011166406,0.00007062715,0.00000977222,0.00002500534,0.00030519004,0.0002944651,0.000044090157,0.9885628,0.0028834569,0.007684897],"study_design_scores_gemma":[0.000003111696,0.0000041742237,0.00017655888,0.000068252564,0.0000032181233,0.00005032965,0.00012068654,0.0003119749,0.00003296814,0.9612791,0.037944477,0.0000051618663],"about_ca_topic_score_codex":0.002804296,"about_ca_topic_score_gemma":0.0016132294,"teacher_disagreement_score":0.009286346,"about_ca_system_score_codex":0.003980014,"about_ca_system_score_gemma":0.0031179192,"threshold_uncertainty_score":0.02887714},"labels":[],"label_agreement":null},{"id":"W2219480549","doi":"10.4018/ijssci.2015040102","title":"Analyze Physical Design Process Using Big Data Tool","year":2015,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Data mining; Data extraction; Process (computing); Data cleansing; Parsing; Data quality; External Data Representation; Data validation; Regular expression; Database; Programming language; Artificial intelligence","score_opus":0.20034241897556992,"score_gpt":0.3961846232129621,"score_spread":0.19584220423739218,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2219480549","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14207166,0.001431437,0.62979543,0.0014105173,0.00032745424,0.0017238907,0.121200874,0.07772684,0.024311915],"genre_scores_gemma":[0.38879678,0.0015251047,0.43922794,0.00030756046,0.00008818413,0.0028056079,0.15069562,0.0028282548,0.013724896],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99808025,0.00017494013,0.00025202383,0.00030717562,0.0010935067,0.000092070026],"domain_scores_gemma":[0.9963296,0.0013349747,0.00040019114,0.00085737364,0.0009444494,0.00013346634],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001543018,0.0013602717,0.0009067294,0.0043122713,0.00055356795,0.0019775662,0.0013028416,0.000663864,0.010260798],"category_scores_gemma":[0.005124186,0.00069443916,0.0014399176,0.0030588664,0.00036345405,0.0017169948,0.0008994529,0.0009809579,0.0032214643],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009013429,0.0010160238,0.083831385,0.004518504,0.00049408694,0.001977162,0.0017023474,0.2059438,0.034353916,0.016828239,0.09920516,0.549228],"study_design_scores_gemma":[0.00017801023,0.00075032323,0.05115611,0.00035463332,0.00023375965,0.0010240545,0.0010538821,0.6456359,0.099292375,0.027246842,0.17281972,0.00025442193],"about_ca_topic_score_codex":0.0025356445,"about_ca_topic_score_gemma":0.0034265528,"teacher_disagreement_score":0.010260798,"about_ca_system_score_codex":0.0006894095,"about_ca_system_score_gemma":0.0015865458,"threshold_uncertainty_score":0.03432578},"labels":[],"label_agreement":null},{"id":"W2414051397","doi":"10.4018/ijssci.2015070102","title":"Multifractal Singularity Spectrum for Cognitive Cyber Defence in Internet Time Series","year":2015,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Research Manitoba; University of Manitoba","funders":"","keywords":"Cyberspace; Computer science; Computer security; Exploit; Hacker; The Internet; Cloud computing; Intrusion detection system; Malware; World Wide Web","score_opus":0.043696728985830845,"score_gpt":0.2795739345611581,"score_spread":0.23587720557532724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2414051397","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0648882,0.0011908202,0.9307243,0.00041946804,0.00009375088,0.000028208939,0.000058960806,0.00015155283,0.002444733],"genre_scores_gemma":[0.9220552,0.0015289477,0.073060505,0.00012863659,0.0002641209,0.000055932713,0.00012447688,0.000052288186,0.0027299197],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996215,0.00015158196,0.000017950208,0.00007294397,0.0001000681,0.000035798173],"domain_scores_gemma":[0.9973097,0.0019566684,0.00026396362,0.0001575273,0.00019629249,0.000115935116],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013999456,0.0006281949,0.00050821074,0.0013252622,0.00032611043,0.00078668963,0.00064136845,0.0007840363,0.0014136961],"category_scores_gemma":[0.007456379,0.00017667301,0.0007451334,0.0008333895,0.0011044823,0.0013863906,0.0006499713,0.0012769179,0.0002537968],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016084204,0.00012752065,0.0076291445,0.00038890846,0.00018464493,0.00084392383,0.0006679168,0.45104477,0.016132796,0.3989831,0.0029073516,0.12092912],"study_design_scores_gemma":[0.0000020585535,0.000021238498,0.001163656,0.000009743326,0.0000094549005,0.00006386171,0.000022768616,0.9763638,0.0002534142,0.021676904,0.0004003793,0.000012879367],"about_ca_topic_score_codex":0.0022051863,"about_ca_topic_score_gemma":0.0011970932,"teacher_disagreement_score":0.0022051863,"about_ca_system_score_codex":0.00052528834,"about_ca_system_score_gemma":0.00035232207,"threshold_uncertainty_score":0.0074037313},"labels":[],"label_agreement":null},{"id":"W2567383190","doi":"10.4018/ijssci.2016100101","title":"Zero-Crossing Analysis of Lévy Walks and a DDoS Dataset for Real-Time Feature Extraction","year":2016,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Diffusion and Search Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Research Manitoba; University of Manitoba","funders":"","keywords":"Computer science; Denial-of-service attack; Algorithm; Noise (video); Computation; Zero crossing; Pattern recognition (psychology); Data mining; Artificial intelligence; The Internet","score_opus":0.015411384252938098,"score_gpt":0.3488662340207575,"score_spread":0.3334548497678194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2567383190","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7339145,0.0008651679,0.24383572,0.00046157028,0.00021080357,0.0003019161,0.011471225,0.0057431553,0.0031960565],"genre_scores_gemma":[0.92584556,0.00017900272,0.06281722,0.000053454485,0.000045261826,0.0001374033,0.010228622,0.00008035465,0.00061312056],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99929845,0.00010067028,0.00010344449,0.00016082385,0.00024392839,0.000092725706],"domain_scores_gemma":[0.9978999,0.00084928155,0.0003449271,0.000341206,0.00044701013,0.00011755127],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010273937,0.000599605,0.00053070625,0.004675514,0.00035213734,0.0008109199,0.0005098417,0.00075205276,0.0007964699],"category_scores_gemma":[0.005263868,0.00010511356,0.0005819901,0.0031816456,0.00029254303,0.0007524413,0.00049929606,0.0005275714,0.0005407754],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012921075,0.0009859274,0.11026058,0.00079277495,0.00040143364,0.0030898876,0.00046973946,0.2590993,0.06536526,0.011736073,0.031168064,0.5153388],"study_design_scores_gemma":[0.00002273659,0.00024056813,0.048968676,0.000030405341,0.000024747884,0.0009435849,0.00020794079,0.92748713,0.01220766,0.004701257,0.005116514,0.000048912523],"about_ca_topic_score_codex":0.002128897,"about_ca_topic_score_gemma":0.002119973,"teacher_disagreement_score":0.004675514,"about_ca_system_score_codex":0.00044739264,"about_ca_system_score_gemma":0.00043366852,"threshold_uncertainty_score":0.00543344},"labels":[],"label_agreement":null},{"id":"W2568490940","doi":"10.4018/ijssci.2017010104","title":"An Artificial Intelligence-Based Vehicular System Simulator","year":2017,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Simulation; Human–computer interaction; Artificial intelligence","score_opus":0.0368538605243459,"score_gpt":0.3293030671005497,"score_spread":0.29244920657620377,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2568490940","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0985057,0.00018358893,0.84599924,0.00028075028,0.00022774002,0.00092091796,0.0013306078,0.012210262,0.04034118],"genre_scores_gemma":[0.7230754,0.00035702207,0.24941862,0.0001229901,0.000027284685,0.0008381607,0.002824947,0.0006688345,0.022666685],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997707,0.00006736048,0.000017788932,0.000028497696,0.00009306256,0.000022662824],"domain_scores_gemma":[0.9995701,0.00017355722,0.00002447242,0.00005992831,0.000109049804,0.00006292603],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036319395,0.0004342021,0.00031141998,0.00032016577,0.0003302777,0.00075499644,0.0012868998,0.00060433714,0.006221929],"category_scores_gemma":[0.001372821,0.00023861132,0.00033937668,0.0002303738,0.00033861946,0.00063391123,0.0008806109,0.0006725762,0.0009647199],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00051133044,0.00029094054,0.0035015265,0.0003720221,0.000101795325,0.00042957728,0.0006932669,0.85166264,0.030884132,0.041488484,0.010490114,0.059574157],"study_design_scores_gemma":[0.00009725589,0.00016526453,0.00045609465,0.000020534175,0.000026336347,0.000088123175,0.000049052567,0.94523007,0.007212059,0.0039510685,0.042677104,0.000027046857],"about_ca_topic_score_codex":0.0049267444,"about_ca_topic_score_gemma":0.003761954,"teacher_disagreement_score":0.006221929,"about_ca_system_score_codex":0.00044099538,"about_ca_system_score_gemma":0.0011053871,"threshold_uncertainty_score":0.020814419},"labels":[],"label_agreement":null},{"id":"W2787471771","doi":"10.4018/ijssci.2018010101","title":"Cognitive Computing","year":2018,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Cognitive computing; Computer science; Cognition; Cognitive robotics; Field (mathematics); Informatics; Artificial intelligence; Cognitive science; Theme (computing); Data science; Embodied cognition; Psychology; World Wide Web; Engineering","score_opus":0.027842110348193786,"score_gpt":0.3335650878012014,"score_spread":0.30572297745300764,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2787471771","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0054504815,0.019862043,0.15980977,0.019671991,0.0030182286,0.0003096909,0.0011537669,0.0022535296,0.78847057],"genre_scores_gemma":[0.416168,0.051406637,0.19515252,0.016610594,0.0059921867,0.0012845271,0.0046613244,0.0012042075,0.30751988],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984457,0.00036600698,0.00008851914,0.0003331222,0.0006161804,0.00015040563],"domain_scores_gemma":[0.9980159,0.0006329222,0.00008365018,0.0005916248,0.00045733448,0.00021863666],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011113796,0.0010766411,0.000670889,0.001636659,0.0016109677,0.007644557,0.0019020387,0.0018941857,0.039908208],"category_scores_gemma":[0.0057577644,0.00031254074,0.0007658405,0.0014360402,0.0035532129,0.0059039006,0.0039960076,0.0021931056,0.013466756],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026635285,0.000027810602,0.0003311044,0.0003922726,0.00004226,0.00011055822,0.0004570435,0.0013034057,0.00061308965,0.8129059,0.06664168,0.11714819],"study_design_scores_gemma":[0.000010015508,0.000017808148,0.00025887252,0.00020162387,0.0000135782375,0.0002106426,0.00020537362,0.0020882613,0.00039641676,0.58495134,0.41162607,0.00002007304],"about_ca_topic_score_codex":0.0022755123,"about_ca_topic_score_gemma":0.001708658,"teacher_disagreement_score":0.039908208,"about_ca_system_score_codex":0.0019049692,"about_ca_system_score_gemma":0.0025364198,"threshold_uncertainty_score":0.13350624},"labels":[],"label_agreement":null},{"id":"W2789779418","doi":"10.4018/ijssci.2018040105","title":"A Fine-Grained Stateful Data Analytics Method Based on Resilient State Table","year":2018,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Stateful firewall; Computer science; SPARK (programming language); Scalability; Big data; Granularity; Programming paradigm; Distributed computing; Database; Data mining; Operating system; Programming language; Computer network","score_opus":0.04559937843690572,"score_gpt":0.34583026390919863,"score_spread":0.30023088547229293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2789779418","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0068451045,0.00014550355,0.9812252,0.000237218,0.000094052266,0.00013088185,0.0002578968,0.009598991,0.0014650546],"genre_scores_gemma":[0.3110129,0.00036140447,0.67916036,0.00035064403,0.00011327312,0.00038011224,0.0015020669,0.000883675,0.0062355595],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99896824,0.00011275939,0.00010900182,0.00031128133,0.0003674373,0.00013133616],"domain_scores_gemma":[0.99870706,0.00028747384,0.00009841521,0.0005321636,0.00028110042,0.00009375882],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009189567,0.0007291909,0.0007858524,0.0015759036,0.0010504159,0.002250731,0.0021908612,0.00055618986,0.0039242343],"category_scores_gemma":[0.0025147172,0.00053317705,0.0012693064,0.001744801,0.000955654,0.0043061273,0.00246497,0.0014215601,0.0009294717],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008680897,0.00032445195,0.0046389005,0.0004634724,0.00018086203,0.00053495175,0.0014907194,0.11356139,0.048117056,0.17719124,0.032258756,0.6203701],"study_design_scores_gemma":[0.00009893989,0.00014412963,0.0005178777,0.000035955516,0.00009316328,0.0002555564,0.00016375056,0.8753026,0.033655494,0.057447534,0.032169778,0.00011526566],"about_ca_topic_score_codex":0.0059488188,"about_ca_topic_score_gemma":0.005285123,"teacher_disagreement_score":0.0059488188,"about_ca_system_score_codex":0.00087531167,"about_ca_system_score_gemma":0.0022668585,"threshold_uncertainty_score":0.013127804},"labels":[],"label_agreement":null},{"id":"W2790979283","doi":"10.4018/ijssci.2018040103","title":"Nuclei Segmentation for Quantification of Brain Tumors in Digital Pathology Images","year":2018,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Segmentation; Computer science; Artificial intelligence; HSL and HSV; Pattern recognition (psychology); Hue; Digital pathology; Image segmentation; Color space; Set (abstract data type); Computer vision; Image (mathematics); Medicine","score_opus":0.04427608283249057,"score_gpt":0.3415510458747453,"score_spread":0.2972749630422547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2790979283","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.054577343,0.000457313,0.9419629,0.00010343346,0.000033661236,0.00013357944,0.00016829126,0.0014243146,0.001139205],"genre_scores_gemma":[0.2702845,0.00048436614,0.7270689,0.000057529036,0.000030448084,0.000107886706,0.0004764202,0.00028428316,0.0012056949],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994815,0.000084553336,0.00004175635,0.00012738994,0.00021602037,0.000048860922],"domain_scores_gemma":[0.99925977,0.000282342,0.00011738009,0.000089175,0.00021190812,0.00003949396],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00077703426,0.00061513024,0.00048834935,0.0029156115,0.0003441451,0.0011056445,0.0007025265,0.00075800664,0.0012546136],"category_scores_gemma":[0.0021353501,0.0003991269,0.00072015106,0.0010494931,0.00050651137,0.0010194766,0.000691914,0.0004195987,0.00074061885],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046053753,0.000101617065,0.008881192,0.00047974742,0.0001411975,0.00023026754,0.0004387043,0.030923275,0.33330876,0.006157007,0.00217608,0.6167016],"study_design_scores_gemma":[0.000027308133,0.0001949077,0.0108504,0.0000561596,0.00013344946,0.0012475455,0.00028125764,0.66168976,0.31247932,0.006366317,0.0066059823,0.000067589055],"about_ca_topic_score_codex":0.0026029637,"about_ca_topic_score_gemma":0.003310844,"teacher_disagreement_score":0.0029156115,"about_ca_system_score_codex":0.0005497815,"about_ca_system_score_gemma":0.0008528206,"threshold_uncertainty_score":0.0051755905},"labels":[],"label_agreement":null},{"id":"W2792789838","doi":"10.4018/ijssci.2017100102","title":"Human Identification Using Gait Skeletal Joint Distance Features","year":2017,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Gait Recognition and Analysis","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"University of Calgary","keywords":"Biometrics; Gait; Computer science; Identification (biology); Artificial intelligence; Pattern recognition (psychology); Joint (building); Feature (linguistics); Feature vector; Support vector machine; Gait analysis; Computer vision; Physical medicine and rehabilitation","score_opus":0.03448649064294875,"score_gpt":0.32190154624510486,"score_spread":0.28741505560215613,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2792789838","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5077507,0.0017958866,0.47782385,0.00019871401,0.00022422137,0.0001325667,0.0015706192,0.0016941226,0.008809279],"genre_scores_gemma":[0.94098043,0.00045310112,0.054795478,0.00003823951,0.00004459605,0.00003446474,0.00092775014,0.000026537746,0.002699325],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997254,0.000032791624,0.0000234545,0.00009861896,0.0000931102,0.000026651951],"domain_scores_gemma":[0.9998005,0.000029669485,0.00005264218,0.000024909365,0.00007797108,0.000014325417],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001668353,0.0003277336,0.00041307425,0.0017982175,0.00014913936,0.00036595808,0.00020673212,0.00040337985,0.001284165],"category_scores_gemma":[0.0007333457,0.00012160425,0.00028567913,0.0011416989,0.00012625576,0.00048780272,0.00034035035,0.00018302194,0.0008088821],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004064178,0.0001697912,0.029270547,0.0002836085,0.00013404795,0.00048352338,0.000118021475,0.014121202,0.08919176,0.0018800492,0.0047863456,0.8591547],"study_design_scores_gemma":[0.000038036196,0.00056751596,0.21411264,0.00012880198,0.00015473671,0.004202449,0.0003815957,0.70517266,0.05719626,0.0057272804,0.012185392,0.00013266483],"about_ca_topic_score_codex":0.0011904779,"about_ca_topic_score_gemma":0.001475402,"teacher_disagreement_score":0.0017982175,"about_ca_system_score_codex":0.00011737232,"about_ca_system_score_gemma":0.00015638818,"threshold_uncertainty_score":0.004295945},"labels":[],"label_agreement":null},{"id":"W2807749681","doi":"10.4018/ijssci.2018070103","title":"Application of Structural Properties of Seismic Data to Prediction of Hydrocarbon Distribution","year":2018,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Comparability; Petroleum engineering; Petroleum; Geology; Computer science; Facies; Fossil fuel; Block (permutation group theory); Structural basin; Geomorphology","score_opus":0.04306730036485026,"score_gpt":0.3041778601560872,"score_spread":0.261110559791237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2807749681","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3788164,0.00040781285,0.6163053,0.00022617326,0.00003959024,0.00004208941,0.0011222676,0.00094832946,0.0020920113],"genre_scores_gemma":[0.94479465,0.00024696093,0.05346181,0.000011020592,0.000030062623,0.00002202031,0.0008595346,0.000036906953,0.0005369876],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99981683,0.000036752688,0.000012421216,0.000045259385,0.00007362918,0.000015175544],"domain_scores_gemma":[0.998706,0.00064261485,0.00018550371,0.000102790924,0.00031365146,0.00004946244],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034898715,0.0005914149,0.00027198522,0.0018736994,0.00014927197,0.0003491264,0.00024160292,0.00038484624,0.0006481193],"category_scores_gemma":[0.0029115968,0.000250042,0.0003024992,0.0012021048,0.000179015,0.0006863199,0.0002606336,0.00036675174,0.00036709715],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016100194,0.00012568355,0.05489826,0.00013785758,0.00007694613,0.00014748522,0.00006899598,0.609247,0.02811414,0.0016971795,0.000894132,0.30443135],"study_design_scores_gemma":[0.0000019027298,0.000021902113,0.005822589,0.0000047291264,0.000008144963,0.000023824294,0.000014223015,0.98944294,0.003764638,0.00060564344,0.00028548678,0.0000039982383],"about_ca_topic_score_codex":0.0033754571,"about_ca_topic_score_gemma":0.0035753574,"teacher_disagreement_score":0.0033754571,"about_ca_system_score_codex":0.00026468112,"about_ca_system_score_gemma":0.00036886169,"threshold_uncertainty_score":0.006711662},"labels":[],"label_agreement":null},{"id":"W2915445509","doi":"10.4018/ijssci.2018100102","title":"Preventing Model Overfitting and Underfitting in Convolutional Neural Networks","year":2018,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":98,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Overfitting; Computer science; Artificial intelligence; Convolutional neural network; Regularization (linguistics); Machine learning; Adaptability; Deep learning; Pattern recognition (psychology); Set (abstract data type); Artificial neural network","score_opus":0.02465964199239385,"score_gpt":0.3058860702326626,"score_spread":0.2812264282402688,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2915445509","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0677589,0.0009260911,0.9277732,0.0008236433,0.00007805006,0.000061271305,0.00004916231,0.0011784753,0.0013511433],"genre_scores_gemma":[0.80718416,0.0009980561,0.18850379,0.00065114617,0.000069999995,0.0002299703,0.00027086868,0.0005368256,0.0015552678],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9963223,0.00152656,0.00032799816,0.0005060279,0.0010621316,0.00025493515],"domain_scores_gemma":[0.98007625,0.013667843,0.00171884,0.002612917,0.0016810434,0.00024309476],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008505819,0.0014791095,0.0018052765,0.0012692206,0.00084265036,0.0016263237,0.0018485722,0.0017743306,0.0008948339],"category_scores_gemma":[0.052121595,0.0010817467,0.0012796634,0.0008504834,0.0022325232,0.0030544067,0.0028776447,0.0032288914,0.00023735515],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020347856,0.00009874041,0.0061408854,0.00035000042,0.00025847091,0.00035723386,0.00030321107,0.8616459,0.006786031,0.029286861,0.0018856865,0.09268352],"study_design_scores_gemma":[0.000007963242,0.000050661904,0.0003863312,0.00004280742,0.000026547405,0.00006385305,0.000023868784,0.9763179,0.0037089635,0.018872077,0.00048587908,0.000013323665],"about_ca_topic_score_codex":0.003912392,"about_ca_topic_score_gemma":0.005189976,"teacher_disagreement_score":0.008505819,"about_ca_system_score_codex":0.00139074,"about_ca_system_score_gemma":0.0021101546,"threshold_uncertainty_score":0.044983625},"labels":[],"label_agreement":null},{"id":"W2916601121","doi":"10.4018/ijssci.2018100101","title":"Saliency Priority of Individual Bottom-Up Attributes in Designing Visual Attention Models","year":2018,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Artificial intelligence; Salient; Ranking (information retrieval); Human visual system model; Motion (physics); Perception; Feature (linguistics); Benchmark (surveying); Cognition; Eye tracking; Affect (linguistics); Visual attention; Human motion; Visual search; Machine learning; Computer vision; Cognitive psychology; Image (mathematics); Psychology","score_opus":0.043152901216286586,"score_gpt":0.34161837885822693,"score_spread":0.29846547764194037,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2916601121","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10667017,0.0004530812,0.8883629,0.00022948843,0.000056752502,0.00019040742,0.000053656706,0.0003988803,0.0035846066],"genre_scores_gemma":[0.9340284,0.00014422706,0.06465865,0.00004855449,0.00004021675,0.00011391838,0.000035012632,0.000030775496,0.000900183],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995555,0.00013236047,0.000026057882,0.00009790338,0.0000950604,0.000093021066],"domain_scores_gemma":[0.99888736,0.00057451846,0.00009372282,0.00007549731,0.000282647,0.000086276326],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013360388,0.0007403994,0.0006587266,0.0010111564,0.0003329063,0.0010569295,0.0011250253,0.0006839425,0.0015139054],"category_scores_gemma":[0.005298388,0.00031751,0.00061149587,0.00041984377,0.0005244936,0.0017577042,0.0007021764,0.0008229316,0.00026269702],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007202476,0.0003403872,0.008562464,0.00045686314,0.00022267047,0.00026806063,0.00091791246,0.5792345,0.067143396,0.058662213,0.0021096168,0.2813617],"study_design_scores_gemma":[0.000012727531,0.00012700485,0.001381266,0.000013029082,0.00003439958,0.000031099786,0.000040890038,0.98572785,0.0032138668,0.008977451,0.00042559783,0.000014861243],"about_ca_topic_score_codex":0.0054220865,"about_ca_topic_score_gemma":0.0044409526,"teacher_disagreement_score":0.0054220865,"about_ca_system_score_codex":0.001183569,"about_ca_system_score_gemma":0.0006546111,"threshold_uncertainty_score":0.01078105},"labels":[],"label_agreement":null},{"id":"W2940891384","doi":"10.4018/ijssci.2019010102","title":"Evaluating the Effects of Size and Precision of Training Data on ANN Training Performance for the Prediction of Chaotic Time Series Patterns","year":2019,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Chaotic; Artificial neural network; Training (meteorology); Time series; Mean squared error; Attractor; Artificial intelligence; Nonlinear system; Series (stratigraphy); Machine learning; Pattern recognition (psychology); Mathematics; Statistics","score_opus":0.07629571614617801,"score_gpt":0.35016898690959725,"score_spread":0.2738732707634192,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2940891384","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9417475,0.0017686624,0.053305306,0.00024408601,0.00014493304,0.00012313781,0.00016224364,0.0005095256,0.0019945824],"genre_scores_gemma":[0.97551835,0.0003497387,0.023402024,0.00003271499,0.000016089396,0.00005903357,0.00019047693,0.000043277912,0.00038832883],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986749,0.0003985186,0.0002415725,0.00024883045,0.0003519486,0.00008421128],"domain_scores_gemma":[0.9770558,0.017343359,0.0011157617,0.0017084135,0.002608654,0.00016806506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035460468,0.0008738151,0.0005534484,0.00048413902,0.00034323192,0.00061759964,0.00049243716,0.0010048877,0.0005096785],"category_scores_gemma":[0.02797261,0.0002817164,0.00036236443,0.00046986938,0.00042899698,0.0011512932,0.00038715138,0.0006591599,0.00015945468],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0037857129,0.0011021346,0.03828405,0.0008717941,0.00038643263,0.0006302353,0.00040412295,0.6064572,0.07775999,0.00078352075,0.0008907675,0.268644],"study_design_scores_gemma":[0.000099676225,0.0027507518,0.03608801,0.00015001751,0.00022996533,0.0002602675,0.00017758975,0.8671212,0.09168314,0.0005018588,0.0008636783,0.00007373337],"about_ca_topic_score_codex":0.0020200028,"about_ca_topic_score_gemma":0.0016620781,"teacher_disagreement_score":0.0035460468,"about_ca_system_score_codex":0.00027043687,"about_ca_system_score_gemma":0.00040370165,"threshold_uncertainty_score":0.018753469},"labels":[],"label_agreement":null},{"id":"W2998967378","doi":"10.4018/ijssci.2019100101","title":"Convolutional Approach Also Benefits Traditional Face Pattern Recognition Algorithm [208!]","year":2019,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Face recognition and analysis","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Northern British Columbia","funders":"","keywords":"Computer science; Convolutional neural network; Facial recognition system; Artificial intelligence; Face (sociological concept); Deep learning; Scope (computer science); Field (mathematics); Pattern recognition (psychology); Machine learning; Algorithm; Mathematics","score_opus":0.04012206773272515,"score_gpt":0.26619851944940837,"score_spread":0.22607645171668322,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2998967378","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014596696,0.00090094376,0.9699112,0.00041193454,0.00024859194,0.00007343523,0.00020108852,0.0022928647,0.011363253],"genre_scores_gemma":[0.3316687,0.0022930035,0.63883317,0.00061509636,0.00025276857,0.00016919151,0.000952035,0.0004040812,0.024812048],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99972504,0.000024024099,0.000017414231,0.000088278095,0.00010930161,0.0000359236],"domain_scores_gemma":[0.9997384,0.000039500028,0.000021670565,0.0000621454,0.00012342507,0.00001476477],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002250268,0.00077395554,0.0004865746,0.0007608965,0.000359564,0.0006880003,0.00093947025,0.00073130545,0.0050077797],"category_scores_gemma":[0.0007518063,0.00021449615,0.00057201774,0.0008365896,0.00041674115,0.0011646089,0.0005722081,0.00083344075,0.0025610938],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011326542,0.0000929675,0.0018217323,0.00028705594,0.00010562847,0.00018535457,0.000067657485,0.028576903,0.048765533,0.029094921,0.010367843,0.8805212],"study_design_scores_gemma":[0.000025589023,0.0002522049,0.0043088305,0.00006576184,0.0001487769,0.0013633599,0.00008625241,0.77562106,0.10117765,0.031727817,0.08514191,0.00008076118],"about_ca_topic_score_codex":0.0049549914,"about_ca_topic_score_gemma":0.0065159523,"teacher_disagreement_score":0.0050077797,"about_ca_system_score_codex":0.00055697316,"about_ca_system_score_gemma":0.0006766075,"threshold_uncertainty_score":0.01675266},"labels":[],"label_agreement":null},{"id":"W3009196551","doi":"10.4018/ijssci.2020010104","title":"An Incentive Compatible Mechanism for Replica Placement in Peer-Assisted Content Distribution","year":2020,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Peer-to-Peer Network Technologies","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Replica; Computer science; Content delivery; Incentive; Distributed computing; Content distribution; Latency (audio); Key (lock); Incentive compatibility; The Internet; Peer-to-peer; Content delivery network; Computer network; World Wide Web; Computer security; Telecommunications; Server","score_opus":0.06765365080020397,"score_gpt":0.3309161150700873,"score_spread":0.2632624642698833,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3009196551","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007891212,0.00017688755,0.99015,0.000158899,0.000099631805,0.0001521808,0.000020998155,0.00016996595,0.0011802344],"genre_scores_gemma":[0.49882787,0.00040800162,0.49627346,0.00014703987,0.00021343237,0.00048731547,0.00006436254,0.00006187089,0.0035165802],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9967512,0.0015589333,0.00019394615,0.00050300476,0.00081986946,0.00017308857],"domain_scores_gemma":[0.9936572,0.0034416209,0.00073929515,0.0009503272,0.0008953379,0.0003162389],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0051675765,0.0007116029,0.0014680513,0.00089697645,0.001380339,0.0012954738,0.0034128926,0.001788288,0.0021852092],"category_scores_gemma":[0.0129435845,0.0005572421,0.000752623,0.001327935,0.0012650099,0.0025909534,0.0018695234,0.0016269138,0.0004717714],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006013995,0.00046352734,0.0012647618,0.00045165076,0.00017187755,0.0005051601,0.00048992364,0.35805732,0.022867052,0.3796789,0.005248723,0.23019971],"study_design_scores_gemma":[0.00017851149,0.00045659562,0.00021483736,0.000026781128,0.000045747183,0.00036283172,0.00004090771,0.9285819,0.0041371295,0.05810277,0.0077958684,0.00005628664],"about_ca_topic_score_codex":0.00061634,"about_ca_topic_score_gemma":0.00063084683,"teacher_disagreement_score":0.0051675765,"about_ca_system_score_codex":0.0010526372,"about_ca_system_score_gemma":0.0020174398,"threshold_uncertainty_score":0.027329087},"labels":[],"label_agreement":null},{"id":"W3013330614","doi":"10.4018/ijssci.2020040105","title":"Population Based Equilibrium in Hybrid SA/PSO for Combinatorial Optimization","year":2020,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Benchmark (surveying); Simulated annealing; Mathematical optimization; Computer science; Particle swarm optimization; Convergence (economics); Combinatorial optimization; Population; Swarm behaviour; Algorithm; Mathematics","score_opus":0.035049917283533495,"score_gpt":0.324975396373623,"score_spread":0.2899254790900895,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3013330614","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010917403,0.000571667,0.9823866,0.00007369103,0.0000669937,0.000052329367,0.000011723603,0.00034364636,0.00557595],"genre_scores_gemma":[0.44039,0.0007386448,0.5534063,0.00015464766,0.000071653856,0.00030908937,0.00007434887,0.00016028938,0.004695],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994129,0.00024156985,0.00002895637,0.00006924248,0.00020697295,0.000040427316],"domain_scores_gemma":[0.9996809,0.00017567897,0.000025685971,0.000033348013,0.000071971204,0.000012424277],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009960671,0.0005678161,0.00061579637,0.0007013682,0.00039019837,0.0010805653,0.0009475238,0.0008644797,0.0014669389],"category_scores_gemma":[0.0015403492,0.00041928026,0.0006069891,0.00055094424,0.0006033944,0.000816493,0.00078575657,0.0009886515,0.0005339429],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000080805126,0.00009041412,0.0008423232,0.00015227648,0.00014974976,0.0001309643,0.00014813404,0.8033413,0.009968001,0.06848533,0.0010204103,0.115590215],"study_design_scores_gemma":[0.000013510566,0.000064426786,0.00011846635,0.000011836488,0.000017378161,0.0000401505,0.000012708074,0.98779047,0.0017667847,0.00683386,0.0033202362,0.000010216854],"about_ca_topic_score_codex":0.0020935666,"about_ca_topic_score_gemma":0.002029789,"teacher_disagreement_score":0.0020935666,"about_ca_system_score_codex":0.00045755092,"about_ca_system_score_gemma":0.0005708484,"threshold_uncertainty_score":0.005267799},"labels":[],"label_agreement":null},{"id":"W3096231919","doi":"10.4018/ijssci.2021010102","title":"Cancer Classification From DNA Microarray Using Genetic Algorithms and Case-Based Reasoning","year":2020,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Mahalanobis distance; Computer science; Classifier (UML); Artificial intelligence; Pattern recognition (psychology); Data mining; Benchmark (surveying); Machine learning; Algorithm","score_opus":0.04315659152290458,"score_gpt":0.3291406945732117,"score_spread":0.28598410305030714,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3096231919","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04225661,0.00056089286,0.9517777,0.0008231855,0.000058397007,0.00037362732,0.00029481782,0.0009998204,0.002855014],"genre_scores_gemma":[0.2824139,0.00046112685,0.714671,0.00021543437,0.0000645793,0.00042233214,0.0007099772,0.000037467133,0.0010042468],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99811506,0.00052604056,0.00022871602,0.00039970252,0.0006336879,0.00009684769],"domain_scores_gemma":[0.99749374,0.0017223386,0.00024300997,0.00016000059,0.0003392165,0.000041604486],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021337597,0.0010462566,0.0011381707,0.0047934903,0.0008058648,0.0020947652,0.0018705887,0.0014199046,0.0017286094],"category_scores_gemma":[0.006496525,0.0005592278,0.0018625658,0.0025500087,0.0008375296,0.001375217,0.00075748924,0.00083130086,0.00029742828],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012527428,0.00036244787,0.007302371,0.0002719242,0.00022863127,0.0006708791,0.00021136367,0.6032618,0.0042502484,0.01737366,0.002490912,0.3634505],"study_design_scores_gemma":[0.000017095643,0.000021294385,0.0004461022,0.000021070879,0.000031066047,0.00011427749,0.000037760878,0.9861292,0.0011782132,0.011184488,0.00080710487,0.000012343299],"about_ca_topic_score_codex":0.009172868,"about_ca_topic_score_gemma":0.0061107073,"teacher_disagreement_score":0.009172868,"about_ca_system_score_codex":0.001801064,"about_ca_system_score_gemma":0.0015623717,"threshold_uncertainty_score":0.018238902},"labels":[],"label_agreement":null},{"id":"W3134022218","doi":"10.4018/ijssci.2021040103","title":"Sharing VM Resources With Using Prediction of Future User Requests for an Efficient Load Balancing in Cloud Computing Environment","year":2021,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Workload; Cloud computing; Load balancing (electrical power); Virtual machine; Distributed computing; Quality of service; Operating system; Computer network","score_opus":0.020331057961904556,"score_gpt":0.2757119111193807,"score_spread":0.25538085315747616,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3134022218","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21920949,0.0007846959,0.7728308,0.0005245942,0.00015458153,0.00016104133,0.00022592045,0.0026868135,0.0034221772],"genre_scores_gemma":[0.9419229,0.00017050357,0.05664773,0.000064765554,0.000046958783,0.000040963183,0.00016949807,0.000058588696,0.00087812176],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993905,0.00011767365,0.000037927297,0.00017909223,0.00017881166,0.00009607587],"domain_scores_gemma":[0.9994923,0.000118100856,0.000084609266,0.00012537921,0.00012531466,0.00005422124],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005817536,0.0007251965,0.00093919365,0.0007320487,0.0006496896,0.0012059652,0.001006121,0.0004903114,0.0007767414],"category_scores_gemma":[0.0014592584,0.00027631276,0.0004203804,0.0009165228,0.00024056487,0.0018409947,0.0005539049,0.00046683208,0.00035553557],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005238275,0.00044483063,0.011802927,0.00012939001,0.00019395984,0.00023438959,0.00022328443,0.56807667,0.04617317,0.0034554142,0.004520663,0.36422154],"study_design_scores_gemma":[0.0000052713117,0.000045615074,0.0008608916,0.000004118603,0.000015324857,0.000038582428,0.00003467109,0.9935203,0.003545329,0.0012425684,0.0006759958,0.000011353981],"about_ca_topic_score_codex":0.0051305,"about_ca_topic_score_gemma":0.005951461,"teacher_disagreement_score":0.0051305,"about_ca_system_score_codex":0.00052755437,"about_ca_system_score_gemma":0.0010778271,"threshold_uncertainty_score":0.010201275},"labels":[],"label_agreement":null},{"id":"W3175593498","doi":"10.4018/jssci.2011100106","title":"The Formal Design Models of Tree Architectures and Behaviors","year":2011,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Tree traversal; Tree (set theory); Binary tree; Node (physics); Process (computing); Set (abstract data type); Architecture; Theoretical computer science; Programming language; Mathematics","score_opus":0.05447491827467927,"score_gpt":0.29095617083677683,"score_spread":0.23648125256209757,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3175593498","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0020177707,0.00029125673,0.99291795,0.00025040368,0.000036496032,0.00007554635,0.000096330456,0.00022521925,0.0040890104],"genre_scores_gemma":[0.083983116,0.0016713478,0.9069832,0.00030998074,0.00012173543,0.0009434941,0.00045481182,0.00021103579,0.0053212484],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973193,0.0007689025,0.00029101426,0.0004132584,0.0010409215,0.00016664212],"domain_scores_gemma":[0.9962419,0.0016791727,0.00042770806,0.0009172196,0.0006388202,0.000095180614],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002819765,0.00090594223,0.00059121393,0.0011257076,0.0010732153,0.0035720565,0.0025152746,0.0014343016,0.0038533884],"category_scores_gemma":[0.00614111,0.0009626486,0.0019461596,0.0013227944,0.0042827977,0.0057646395,0.0013269199,0.0033987614,0.0012792819],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000843071,0.000017773365,0.00012357983,0.0001321066,0.000013667035,0.0000707949,0.00031406974,0.017285135,0.0014461646,0.96795446,0.0006876925,0.01194603],"study_design_scores_gemma":[0.00003019864,0.00006894551,0.00015383934,0.00018193659,0.00004912009,0.00028507627,0.00014022374,0.119531624,0.0034012834,0.81364375,0.062475033,0.000038887516],"about_ca_topic_score_codex":0.0026761184,"about_ca_topic_score_gemma":0.0027041915,"teacher_disagreement_score":0.0038533884,"about_ca_system_score_codex":0.0018491598,"about_ca_system_score_gemma":0.0028011014,"threshold_uncertainty_score":0.014912486},"labels":[],"label_agreement":null},{"id":"W422168210","doi":"10.4018/ijssci.2014040103","title":"On a Novel Cognitive Knowledge Base (CKB) for Cognitive Robots and Machine Learning","year":2014,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Knowledge base; Cognitive robotics; Cognition; Cognitive computing; Artificial intelligence; Knowledge acquisition; Ontology; LIDA; Knowledge-based systems; Embodied cognition; Cognitive model; Human–computer interaction; Knowledge management; Psychology","score_opus":0.03921022212491013,"score_gpt":0.3203578662171045,"score_spread":0.2811476440921944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W422168210","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0064728805,0.0011429966,0.9629497,0.0027077857,0.0002341511,0.00015012617,0.00029302793,0.0007507319,0.025298638],"genre_scores_gemma":[0.13031177,0.0017266023,0.8561886,0.0010069329,0.00021323915,0.00033832985,0.00082791556,0.0001407453,0.009245781],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9987973,0.00025758517,0.00011232626,0.00033704098,0.00041995585,0.00007580961],"domain_scores_gemma":[0.9981811,0.00057114364,0.0001404981,0.00051150814,0.00037445297,0.00022130283],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016149199,0.0005291079,0.0007067968,0.0023139569,0.0018960101,0.005828417,0.0023018178,0.0017083049,0.0053047375],"category_scores_gemma":[0.0046742647,0.000554309,0.0012559067,0.0022928647,0.0052218963,0.012366533,0.00468527,0.0025375602,0.0018866182],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029603501,0.000029624798,0.00022100634,0.00013801907,0.000026490516,0.0001643304,0.0005579151,0.00480133,0.001665201,0.9357044,0.0032796774,0.053382378],"study_design_scores_gemma":[0.000027485732,0.000043863223,0.00031898866,0.00017517753,0.000038185717,0.00033480898,0.00021724818,0.047759578,0.0019138507,0.86206955,0.0870476,0.000053645865],"about_ca_topic_score_codex":0.007885163,"about_ca_topic_score_gemma":0.005333951,"teacher_disagreement_score":0.007885163,"about_ca_system_score_codex":0.0015633479,"about_ca_system_score_gemma":0.0027994716,"threshold_uncertainty_score":0.01774609},"labels":[],"label_agreement":null},{"id":"W4285219276","doi":"10.4018/ijssci.300364","title":"A Comparative Study of Generative Adversarial Networks for Text-to-Image Synthesis","year":2022,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Generative grammar; Task (project management); Image (mathematics); Field (mathematics); Image synthesis; Artificial intelligence; Adversarial system; Tree (set theory); Natural language processing; Mathematics","score_opus":0.029652340812840124,"score_gpt":0.31188822673331545,"score_spread":0.2822358859204753,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285219276","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12594701,0.01113516,0.8014396,0.0022131924,0.00046108043,0.00016943738,0.00030518614,0.0013491004,0.056980267],"genre_scores_gemma":[0.89330775,0.0028530364,0.090197854,0.00031770754,0.0001608021,0.000079759964,0.0003686168,0.0002515043,0.012462888],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993773,0.00025845767,0.000023643255,0.00012007769,0.00015904327,0.00006150728],"domain_scores_gemma":[0.99682,0.002599404,0.00009415943,0.0002262918,0.00018944117,0.000070784605],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001893844,0.0008419052,0.0006125006,0.00059768616,0.0002743474,0.00097429025,0.0008269196,0.0010313813,0.004103067],"category_scores_gemma":[0.006078127,0.00029791158,0.0006481104,0.00037315118,0.0007663034,0.0016261814,0.000939008,0.0015118611,0.0006685561],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044064262,0.00012526439,0.00091741525,0.0002246388,0.00013477076,0.00013637602,0.00013835506,0.83497256,0.0050082295,0.04227433,0.002603798,0.113023594],"study_design_scores_gemma":[0.000010542766,0.00009570445,0.0002518266,0.00002365411,0.000014547435,0.000058992344,0.00001955133,0.98726827,0.0019232599,0.0085991,0.0017254194,0.000009205224],"about_ca_topic_score_codex":0.002281687,"about_ca_topic_score_gemma":0.00224196,"teacher_disagreement_score":0.004103067,"about_ca_system_score_codex":0.0010433581,"about_ca_system_score_gemma":0.0004802828,"threshold_uncertainty_score":0.013726115},"labels":[],"label_agreement":null},{"id":"W4360841925","doi":"10.4018/ijssci.320499","title":"Knowledge Discovery of Hospital Medical Technology Based on Partial Ordered Structure Diagrams","year":2023,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan; University of Alberta","funders":"","keywords":"Computer science; Partially ordered set; Diagram; Context (archaeology); Set (abstract data type); Data mining; Algorithm; Theoretical computer science; Discrete mathematics; Mathematics; Database","score_opus":0.015173142686643172,"score_gpt":0.30162872076833835,"score_spread":0.2864555780816952,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4360841925","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.034724228,0.00046164248,0.9577674,0.00048082098,0.00002398763,0.00025476018,0.0008732821,0.00054530136,0.0048684655],"genre_scores_gemma":[0.28280073,0.00082522427,0.71269006,0.00008187505,0.000020585474,0.00029191762,0.0017186395,0.000040561903,0.0015304035],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9970323,0.00075637,0.00032987315,0.00050917757,0.0012504898,0.00012185036],"domain_scores_gemma":[0.99553865,0.0025149044,0.00050277344,0.00032682132,0.0009890369,0.000127817],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016893286,0.00060655276,0.0005721879,0.0073975637,0.0010399465,0.0021520539,0.0010194159,0.0006027159,0.0017082895],"category_scores_gemma":[0.007515826,0.00041634208,0.0015163891,0.004431219,0.0009544388,0.0044121593,0.0011503098,0.00062363315,0.0003027886],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002204002,0.00018616424,0.023247778,0.001567285,0.0003056369,0.0017222964,0.0030384,0.11906366,0.010897104,0.41980603,0.0052015614,0.41474366],"study_design_scores_gemma":[0.000103828024,0.00014991355,0.00553656,0.0003293712,0.00037479054,0.0013599072,0.0011801987,0.61932194,0.017403679,0.29695004,0.05716927,0.000120483164],"about_ca_topic_score_codex":0.008497793,"about_ca_topic_score_gemma":0.007456407,"teacher_disagreement_score":0.008497793,"about_ca_system_score_codex":0.0014558925,"about_ca_system_score_gemma":0.002990158,"threshold_uncertainty_score":0.016896665},"labels":[],"label_agreement":null},{"id":"W765400474","doi":"10.4018/ijssci.2014070102","title":"A Particle Swarm Optimization Approach for Reuse Guided Case Retrieval","year":2014,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Computer science; Particle swarm optimization; Reuse; Case-based reasoning; Process (computing); Recall; Artificial intelligence; Similarity (geometry); Fitness function; Adaptability; Content-addressable memory; Machine learning; Genetic algorithm; Artificial neural network; Programming language","score_opus":0.03889977350895063,"score_gpt":0.317839858165346,"score_spread":0.27894008465639536,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W765400474","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0073176934,0.00018738475,0.9900595,0.00011829991,0.000036671307,0.00007517658,0.000021865199,0.0001805211,0.0020030097],"genre_scores_gemma":[0.36519688,0.0004927845,0.62649363,0.00015986465,0.00007796889,0.00057104306,0.0001927674,0.00008115636,0.006733947],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99975115,0.000065486594,0.000020527012,0.00005081317,0.000084773994,0.000027331878],"domain_scores_gemma":[0.9997559,0.000112835594,0.000026152664,0.000026170426,0.00006492661,0.000014067435],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063421426,0.0008330211,0.001029773,0.0009297671,0.00044927004,0.00093902054,0.0013194513,0.0013140617,0.0021357993],"category_scores_gemma":[0.0013072572,0.00049794436,0.0008457051,0.00094390387,0.00047614923,0.000723729,0.00075071125,0.0007270257,0.00039583488],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038743703,0.00004787116,0.0002737479,0.00004465816,0.000045946585,0.00006135616,0.00004517846,0.9304421,0.0015105617,0.007967031,0.0008636072,0.058659185],"study_design_scores_gemma":[0.0000074179634,0.000012665557,0.000031592605,0.0000018162422,0.000004791737,0.0000073997057,0.0000028403801,0.99868435,0.00013841773,0.0008253001,0.00028079128,0.0000025455467],"about_ca_topic_score_codex":0.009297105,"about_ca_topic_score_gemma":0.0050136894,"teacher_disagreement_score":0.009297105,"about_ca_system_score_codex":0.0006785897,"about_ca_system_score_gemma":0.0009737993,"threshold_uncertainty_score":0.018485963},"labels":[],"label_agreement":null},{"id":"W840160456","doi":"10.4018/ijssci.2014070101","title":"Enhanced Global Best Particle Swarm Classification","year":2014,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Particle swarm optimization; Benchmark (surveying); Centroid; Computer science; Position (finance); Set (abstract data type); Multi-swarm optimization; Swarm behaviour; Algorithm; Space (punctuation); Data mining; Artificial intelligence; Mathematical optimization; Mathematics","score_opus":0.03023629774515694,"score_gpt":0.32091491539140105,"score_spread":0.2906786176462441,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W840160456","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04856771,0.0011455299,0.94201916,0.0002624397,0.0003051309,0.00007891766,0.00015597232,0.0012000066,0.006265106],"genre_scores_gemma":[0.65294975,0.0005228015,0.33576843,0.00028737154,0.0001937835,0.00014125882,0.000709628,0.00020845822,0.009218518],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991008,0.00017254204,0.000053579894,0.00020781562,0.00035493384,0.00011030406],"domain_scores_gemma":[0.9988193,0.0003204816,0.00010838771,0.0002416687,0.0004590722,0.000050998588],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001463425,0.0008847399,0.0017066525,0.0013875054,0.0005228342,0.0016530417,0.0011778628,0.0014987035,0.0022895923],"category_scores_gemma":[0.003055261,0.00026894093,0.00082095043,0.0013315368,0.0004943494,0.0013451608,0.0010660199,0.0008458513,0.00081012445],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003438251,0.00014512033,0.0033931795,0.00015286391,0.00014205162,0.00020677397,0.00015179644,0.33963114,0.008612596,0.008514116,0.008354476,0.63035214],"study_design_scores_gemma":[0.000023571869,0.000075824784,0.00086845993,0.000013078096,0.000024483179,0.0000798729,0.000019438734,0.990519,0.0026713025,0.0023681736,0.0033260356,0.000010877863],"about_ca_topic_score_codex":0.0029857971,"about_ca_topic_score_gemma":0.0022106827,"teacher_disagreement_score":0.0029857971,"about_ca_system_score_codex":0.00051332737,"about_ca_system_score_gemma":0.0006774863,"threshold_uncertainty_score":0.0077394247},"labels":[],"label_agreement":null}]}