{"meta":{"query_hash":"dc5e85179625","filters":{"venue":"International Journal of Applied Decision Sciences"},"cohort_total":7,"direct_labels_cover":0,"predictions_cover":7,"exported":7,"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/dc5e85179625","api":"https://metacan.xera.ac/api/v1/cohort?venue=International+Journal+of+Applied+Decision+Sciences"},"results":[{"id":"W2010895306","doi":"10.1504/ijads.2014.058038","title":"An empirical examination of corporate websites as a voluntary disclosure medium","year":2013,"lang":"en","type":"article","venue":"International Journal of Applied Decision Sciences","topic":"Auditing, Earnings Management, Governance","field":"Business, Management and Accounting","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":"Brock University","funders":"","keywords":"Voluntary disclosure; Business; Accounting; Earnings; Revenue; Capital market; Relevance (law); Investor relations; Turnover; Marketing; Strategic management; Economics; Finance","score_opus":0.026197305319392208,"score_gpt":0.2926694982445252,"score_spread":0.266472192925133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2010895306","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":[0.9850021,0.00039239207,0.0005311197,0.00055236765,0.0000149711705,0.000046811707,0.00016167352,0.000011055178,0.013287518],"genre_scores_gemma":[0.9987338,0.0001820192,0.0003145967,0.000053135704,0.00002105565,0.000015192973,0.00014040656,0.0000036106856,0.00053613033],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99081504,0.004895879,0.00067755056,0.00040106176,0.0027797592,0.00043081536],"domain_scores_gemma":[0.65548563,0.24866958,0.07232871,0.0073622772,0.012198863,0.0039549177],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0075880955,0.00020018841,0.00025010042,0.0026933698,0.0008527812,0.0038941659,0.0006585452,0.00079765177,0.0035260748],"category_scores_gemma":[0.094986774,0.00018971146,0.0002546488,0.0041695037,0.0015467472,0.0042108987,0.0015974302,0.0017639803,0.00043816253],"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":[0.00019804026,0.0008306033,0.9401698,0.0002243153,0.00006670973,0.00026703873,0.0061937505,0.00044952953,0.00043381477,0.008132449,0.0012658975,0.04176801],"study_design_scores_gemma":[0.000023457258,0.00035782187,0.95794153,0.00049147476,0.00012173847,0.00064054923,0.022122884,0.0052166134,0.0011967731,0.0025986023,0.00925083,0.000037614256],"about_ca_topic_score_codex":0.0020447604,"about_ca_topic_score_gemma":0.002260244,"teacher_disagreement_score":0.0075880955,"about_ca_system_score_codex":0.0009338169,"about_ca_system_score_gemma":0.0012864457,"threshold_uncertainty_score":0.04013014},"labels":[],"label_agreement":null},{"id":"W2561895128","doi":"10.1504/ijads.2016.081393","title":"A new heuristic memory-based simulated annealing approach applied to mine production scheduling problem","year":2016,"lang":"en","type":"article","venue":"International Journal of Applied Decision Sciences","topic":"Mining Techniques and Economics","field":"Engineering","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":"McGill University","funders":"","keywords":"Simulated annealing; Mathematical optimization; Computer science; Scheduling (production processes); Heuristic; Job shop scheduling; Algorithm; Mathematics; Schedule","score_opus":0.02678745024188873,"score_gpt":0.2798924677841571,"score_spread":0.2531050175422684,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2561895128","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":[0.02045972,0.00044745512,0.9742681,0.00020505144,0.000063577674,0.000085018655,0.00004930813,0.0002739682,0.0041477326],"genre_scores_gemma":[0.5292533,0.0005454066,0.46451053,0.00014836168,0.000060400143,0.00044690954,0.00015678653,0.00008161507,0.004796792],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996201,0.0001534092,0.0000220671,0.00006751927,0.000083721534,0.000053171494],"domain_scores_gemma":[0.99965227,0.00018982802,0.000040459912,0.000029187408,0.00006687222,0.000021295878],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006024724,0.00064867485,0.001103213,0.00063522207,0.00046996324,0.000821544,0.0012522646,0.0010367424,0.00167344],"category_scores_gemma":[0.0012822339,0.00047119168,0.00091422815,0.00082558865,0.00050119386,0.00057964236,0.00067445624,0.00079695845,0.00022053633],"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":[0.000052528652,0.000022915003,0.00025039568,0.000061562096,0.00003329468,0.000044842385,0.000044567056,0.96708107,0.0018096195,0.0055048093,0.00052722706,0.024567278],"study_design_scores_gemma":[0.000009067231,0.000028791786,0.000051622137,0.0000057020325,0.000009395917,0.000017407914,0.000005894227,0.9972517,0.00044937903,0.001476461,0.00069037586,0.000004287904],"about_ca_topic_score_codex":0.0048528532,"about_ca_topic_score_gemma":0.0040943003,"teacher_disagreement_score":0.0048528532,"about_ca_system_score_codex":0.00068931945,"about_ca_system_score_gemma":0.0013917907,"threshold_uncertainty_score":0.009649217},"labels":[],"label_agreement":null},{"id":"W4255696462","doi":"10.1504/ijads.2017.10002219","title":"A new heuristic memory-based simulated annealing approach applied to mine production scheduling problem","year":2016,"lang":"en","type":"article","venue":"International Journal of Applied Decision Sciences","topic":"Mining Techniques and Economics","field":"Engineering","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":"McGill University","funders":"","keywords":"Simulated annealing; Mathematical optimization; Computer science; Scheduling (production processes); Heuristic; Job shop scheduling; Algorithm; Mathematics; Schedule","score_opus":0.02678745024188873,"score_gpt":0.2798924677841571,"score_spread":0.2531050175422684,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4255696462","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":[0.02045972,0.00044745512,0.9742681,0.00020505144,0.000063577674,0.000085018655,0.00004930813,0.0002739682,0.0041477326],"genre_scores_gemma":[0.5292533,0.0005454066,0.46451053,0.00014836168,0.000060400143,0.00044690954,0.00015678653,0.00008161507,0.004796792],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996201,0.0001534092,0.0000220671,0.00006751927,0.000083721534,0.000053171494],"domain_scores_gemma":[0.99965227,0.00018982802,0.000040459912,0.000029187408,0.00006687222,0.000021295878],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006024724,0.00064867485,0.001103213,0.00063522207,0.00046996324,0.000821544,0.0012522646,0.0010367424,0.00167344],"category_scores_gemma":[0.0012822339,0.00047119168,0.00091422815,0.00082558865,0.00050119386,0.00057964236,0.00067445624,0.00079695845,0.00022053633],"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":[0.000052528652,0.000022915003,0.00025039568,0.000061562096,0.00003329468,0.000044842385,0.000044567056,0.96708107,0.0018096195,0.0055048093,0.00052722706,0.024567278],"study_design_scores_gemma":[0.000009067231,0.000028791786,0.000051622137,0.0000057020325,0.000009395917,0.000017407914,0.000005894227,0.9972517,0.00044937903,0.001476461,0.00069037586,0.000004287904],"about_ca_topic_score_codex":0.0048528532,"about_ca_topic_score_gemma":0.0040943003,"teacher_disagreement_score":0.0048528532,"about_ca_system_score_codex":0.00068931945,"about_ca_system_score_gemma":0.0013917907,"threshold_uncertainty_score":0.009649217},"labels":[],"label_agreement":null},{"id":"W4323967610","doi":"10.1504/ijads.2023.129477","title":"Evaluation of cloud computing risks using an integrated fuzzy-ANP and FMEA approaches","year":2023,"lang":"en","type":"article","venue":"International Journal of Applied Decision Sciences","topic":"Cloud Data Security Solutions","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":"Toronto Metropolitan University","funders":"","keywords":"Risk analysis (engineering); Outsourcing; Cloud computing; Process management; Computer science; Risk management; Audit; Scope (computer science); Business; Accounting; Finance","score_opus":0.36031702245024766,"score_gpt":0.4343285576832485,"score_spread":0.07401153523300086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323967610","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":[0.11077563,0.00044876078,0.876352,0.0002621283,0.000038479928,0.00037007994,0.00015834547,0.0001907277,0.011403788],"genre_scores_gemma":[0.77492994,0.0003164976,0.2224669,0.00004728439,0.000021938842,0.00031166716,0.0001435526,0.00002299,0.0017392252],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989429,0.00037664414,0.0000618133,0.00010649765,0.0003763655,0.0001357201],"domain_scores_gemma":[0.99845815,0.00093988294,0.00016601852,0.000042451098,0.00034315462,0.000050281662],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026965356,0.0013684996,0.0010075249,0.0053135636,0.0009879707,0.002036615,0.0011899349,0.0012262102,0.0023133755],"category_scores_gemma":[0.0038648483,0.00054797606,0.0019847949,0.0015763163,0.0005695085,0.0010087548,0.001071574,0.0006997215,0.0001618659],"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":[0.00008519491,0.00012187034,0.003416752,0.00013996284,0.00013529332,0.00011201116,0.00012614223,0.93950397,0.0013622168,0.007237946,0.0002665429,0.04749216],"study_design_scores_gemma":[0.000006926647,0.000054404103,0.0007493785,0.000029385053,0.000032384683,0.000024534247,0.000099953824,0.9950702,0.00047097425,0.0031392537,0.00031145784,0.000011226087],"about_ca_topic_score_codex":0.020542327,"about_ca_topic_score_gemma":0.014249533,"teacher_disagreement_score":0.020542327,"about_ca_system_score_codex":0.0026441289,"about_ca_system_score_gemma":0.0021185908,"threshold_uncertainty_score":0.040845513},"labels":[],"label_agreement":null},{"id":"W4392400691","doi":"10.1504/ijads.2024.137003","title":"Applying customer intelligence in marketing: a holistic approach","year":2024,"lang":"en","type":"article","venue":"International Journal of Applied Decision Sciences","topic":"Competitive and Knowledge Intelligence","field":"Business, Management and Accounting","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":"Université du Québec à Trois-Rivières","funders":"","keywords":"Marketing; Business; Relationship marketing; Marketing strategy; Customer engagement; Marketing management; Process management; Knowledge management; Industrial organization; Computer science","score_opus":0.06428480714197742,"score_gpt":0.3471221330413613,"score_spread":0.2828373258993839,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392400691","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":[0.060886197,0.041228693,0.38988933,0.03182891,0.0009078794,0.0008109822,0.00021043714,0.0008127684,0.47342473],"genre_scores_gemma":[0.76673704,0.032113984,0.18220937,0.0034383794,0.000625776,0.00039212417,0.00012246767,0.000078603494,0.014282276],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99695504,0.0013384905,0.00013347143,0.00020221218,0.0010938245,0.0002768746],"domain_scores_gemma":[0.99867344,0.000553445,0.00011926592,0.00009379413,0.00039071977,0.00016935593],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028338376,0.0011235693,0.00082276424,0.005487473,0.0018748795,0.015389781,0.0014408852,0.0024407788,0.0020251512],"category_scores_gemma":[0.0019383121,0.0005794251,0.00063875597,0.004673291,0.0057831653,0.010350734,0.0049474696,0.0024119583,0.00060858845],"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":[0.00007538014,0.00028363836,0.005382726,0.0013509986,0.00017416589,0.0006248808,0.0067354986,0.007667693,0.0027527534,0.6061826,0.009099434,0.3596703],"study_design_scores_gemma":[0.000030412342,0.00042671355,0.010267364,0.0029460692,0.00031672322,0.0015473419,0.01825308,0.03302323,0.0038858016,0.7189173,0.21018623,0.00019980741],"about_ca_topic_score_codex":0.0019158553,"about_ca_topic_score_gemma":0.002598432,"teacher_disagreement_score":0.015389781,"about_ca_system_score_codex":0.0037102727,"about_ca_system_score_gemma":0.004558599,"threshold_uncertainty_score":0.02692002},"labels":[],"label_agreement":null},{"id":"W4405511808","doi":"10.1504/ijads.2025.10068509","title":"Minimising makespan and total tardiness in no-wait open-shop scheduling problems using metaheuristic algorithms: a narrative review","year":2024,"lang":"en","type":"review","venue":"International Journal of Applied Decision Sciences","topic":"Scheduling and Optimization Algorithms","field":"Engineering","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":"Dalhousie University","funders":"","keywords":"Tardiness; Job shop scheduling; Metaheuristic; Computer science; Scheduling (production processes); Mathematical optimization; Narrative; Operations research; Algorithm; Mathematics","score_opus":0.08560608207754947,"score_gpt":0.4020833054340306,"score_spread":0.3164772233564811,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405511808","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00021107885,0.9969177,0.0013519201,0.00023616229,0.00012709723,0.000014738285,0.000017009344,0.0000072676394,0.0011171071],"genre_scores_gemma":[0.0023747724,0.9950582,0.0018768412,0.00013743447,0.00012758435,0.000026275393,0.000032360305,0.000004777098,0.00036167106],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993456,0.00015317956,0.00011406615,0.00011517038,0.0002386743,0.00003343913],"domain_scores_gemma":[0.9981781,0.0012875019,0.0001853841,0.00003896029,0.00027754545,0.000032546453],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014702945,0.0012002547,0.0015510087,0.002510926,0.000267592,0.0014555134,0.0012276705,0.0014217733,0.0021982265],"category_scores_gemma":[0.0035651168,0.00056014827,0.001077384,0.003555824,0.00050183444,0.0015954252,0.0005487687,0.0013217378,0.0008733594],"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":[0.00009710749,0.00010229781,0.00022560802,0.06932552,0.00037436615,0.00013301698,0.00011010849,0.007013551,0.0012635111,0.019739201,0.013024998,0.8885908],"study_design_scores_gemma":[0.000042534688,0.00048064432,0.0011470565,0.028983764,0.0007619798,0.0008721757,0.00018979391,0.0037697686,0.0020181707,0.012428877,0.94920826,0.000097119715],"about_ca_topic_score_codex":0.0017876381,"about_ca_topic_score_gemma":0.0021653469,"teacher_disagreement_score":0.002510926,"about_ca_system_score_codex":0.0008055745,"about_ca_system_score_gemma":0.0020458612,"threshold_uncertainty_score":0.0077757835},"labels":[],"label_agreement":null},{"id":"W7115008491","doi":"10.1504/ijads.2026.150373","title":"Minimising makespan and total tardiness in no-wait open-shop scheduling problems using metaheuristic algorithms: a narrative review","year":2025,"lang":"en","type":"article","venue":"International Journal of Applied Decision Sciences","topic":"Scheduling and Optimization Algorithms","field":"Engineering","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":"Dalhousie University","funders":"","keywords":"Tardiness; Metaheuristic; Job shop scheduling; Simulated annealing; Particle swarm optimization; Scheduling (production processes); Integer programming; Novelty; Heuristics","score_opus":0.0350360713101105,"score_gpt":0.3502053889591038,"score_spread":0.3151693176489933,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7115008491","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007568327,0.98568326,0.009319027,0.0009283784,0.00030673866,0.000033281227,0.00003490368,0.000016094886,0.0029215312],"genre_scores_gemma":[0.012156905,0.9761002,0.009953044,0.00039142236,0.0003595931,0.000079080244,0.00006186814,0.00001490813,0.00088295335],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99906284,0.00029322275,0.00015079297,0.00013636632,0.00031949978,0.000037278092],"domain_scores_gemma":[0.9970373,0.002276579,0.00026061144,0.000053846732,0.000336182,0.000035535133],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022052212,0.0010939535,0.001146022,0.0018424463,0.00025972445,0.0018048845,0.0012733581,0.0014673029,0.0015163457],"category_scores_gemma":[0.0058447937,0.00044246492,0.0010368293,0.0026825734,0.00065254775,0.0017503176,0.00053952954,0.0013352063,0.00045337688],"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":[0.00013646133,0.00010120858,0.00039347005,0.06879409,0.00047407264,0.00019137358,0.00022256875,0.029654184,0.0016122396,0.07012852,0.014287312,0.8140044],"study_design_scores_gemma":[0.00005441129,0.00076890626,0.001304172,0.042736553,0.00076662324,0.00087299995,0.00046119702,0.018798823,0.0037417861,0.044378467,0.8859867,0.00012932673],"about_ca_topic_score_codex":0.0017500885,"about_ca_topic_score_gemma":0.001883253,"teacher_disagreement_score":0.0022052212,"about_ca_system_score_codex":0.0011159074,"about_ca_system_score_gemma":0.002601798,"threshold_uncertainty_score":0.011662483},"labels":[],"label_agreement":null}]}