{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":11,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":11,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12","author_layer_release":"2026-06-26"},"query_hash":"2d5858525682","filters":{"venue":"Electronic Imaging"}},"results":[{"id":"W2808673810","doi":"10.2352/issn.2470-1173.2018.09.iriacv-239","title":"Accumulated Relative Density Outlier Detection For Large Scale Traffic Data","year":2018,"lang":"en","type":"article","venue":"Electronic Imaging","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Outlier; Anomaly detection; Local outlier factor; Data set; Mathematics; Data point; Statistics; Principal component analysis; Point (geometry); Scale (ratio); Set (abstract data type); Dimension (graph theory); Pattern recognition (psychology); Computer science; Data mining; Artificial intelligence; Geography; Cartography; Geometry; Combinatorics","authors":[{"name":"Sophia W.T.T. Liu","is_ca":false},{"name":"Henry Y. T. Ngan","is_ca":true},{"name":"Michael K. Ng","is_ca":true},{"name":"Steven J. Simske","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01717890585864737,"gpt":0.2951430971756584,"spread":0.277964191317011,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002735983,0.001161121,0.001530856,0.005098737,0.0006943346,0.001091281,0.001302428,0.0007543701,0.0005036555],"category_scores_gemma":[0.01266976,0.0003090255,0.001042709,0.004037882,0.0007604727,0.001522244,0.00161863,0.001026566,0.0003741675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007356012,"about_ca_system_score_gemma":0.0009712883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004189837,"about_ca_topic_score_gemma":0.003197118,"domain_scores_codex":[0.996348,0.0005664412,0.0003007542,0.0006733139,0.001864921,0.0002466525],"domain_scores_gemma":[0.9924634,0.0029884,0.00133315,0.0009523826,0.002020018,0.0002426965],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007101438,0.0003605462,0.08481147,0.0004800976,0.000475422,0.001495446,0.0006676635,0.3130229,0.03216297,0.007092666,0.004550307,0.5541704],"study_design_scores_gemma":[0.00001418198,0.0001324601,0.01107287,0.00002088639,0.0000396723,0.0004855579,0.0001567057,0.9722197,0.01015583,0.003202727,0.00244687,0.00005251788],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1592324,0.0008531786,0.835517,0.0001638704,0.000131905,0.0001103175,0.0004894804,0.002641476,0.0008605273],"genre_scores_gemma":[0.8267761,0.0004475458,0.1696423,0.00005653931,0.00008576579,0.0001454589,0.001760878,0.0001569975,0.0009283985],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005098737,"threshold_uncertainty_score":0.01446944,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2580777197","doi":"10.2352/issn.2470-1173.2016.12.imse-263","title":"Novel Real-Time Tone-Mapping Operator for Noisy Logarithmic CMOS Image Sensors","year":2016,"lang":"en","type":"article","venue":"Electronic Imaging","topic":"Image Enhancement Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"CMC Microsystems","keywords":"Tone mapping; Fixed-pattern noise; Computer science; Computer vision; Noise (video); Artificial intelligence; Logarithm; Image sensor; Histogram; CMOS; Distortion (music); Dynamic range; Operator (biology); High dynamic range; Image (mathematics); Electronic engineering; Mathematics; Engineering","authors":[{"name":"Jing Li","is_ca":false},{"name":"Orit Skorka","is_ca":false},{"name":"Kamal Ranaweera","is_ca":false},{"name":"Dileepan Joseph","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.006939548437493282,"gpt":0.2595060983415057,"spread":0.2525665499040124,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002663458,0.0003056973,0.0001647613,0.0001505574,0.0001654084,0.0004116652,0.0006124863,0.0002741858,0.001783449],"category_scores_gemma":[0.001234799,0.0001164418,0.0001767623,0.0001499951,0.0003492919,0.0005562092,0.0004119214,0.0003277674,0.0002593293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002086253,"about_ca_system_score_gemma":0.0001789711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002436527,"about_ca_topic_score_gemma":0.0003236222,"domain_scores_codex":[0.9997604,0.00003615247,0.00001279161,0.00005810831,0.000117468,0.00001505037],"domain_scores_gemma":[0.999556,0.0001960209,0.00006016752,0.00005870999,0.0001023077,0.00002665852],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003500177,0.0000491818,0.0005975068,0.0001438623,0.00001539898,0.0002445467,0.000231188,0.005978371,0.7781273,0.007173049,0.001237492,0.2058521],"study_design_scores_gemma":[0.00004931868,0.0007674701,0.001899201,0.00002790085,0.0000405174,0.002168333,0.00009354596,0.2924653,0.6781637,0.003741171,0.02051672,0.00006678814],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03152716,0.0001604734,0.9662904,0.00006475454,0.0000551814,0.00004628165,0.00002148625,0.0005251669,0.001309077],"genre_scores_gemma":[0.4921888,0.0002245003,0.5027553,0.000132386,0.00006124429,0.00006964651,0.00004666913,0.00009390374,0.004427521],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001783449,"threshold_uncertainty_score":0.005966246,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2887188824","doi":"10.2352/issn.2470-1173.2018.06.mobmu-114","title":"An Integration of Health Tracking Sensor Applications and eLearning Environments for Cloud-Based Health Promotion Campaigns","year":2018,"lang":"en","type":"article","venue":"Electronic Imaging","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Bell (Canada)","funders":"National Institute of Nursing Research","keywords":"Cloud computing; Computer science; Scalability; Workflow; Multimedia; The Internet; Android (operating system); World Wide Web; Database; Operating system","authors":[{"name":"Devasena Inupakutika","is_ca":true},{"name":"Girish Vaidyanathan Natarajan","is_ca":true},{"name":"Sahak Kaghyan","is_ca":true},{"name":"David Akopian","is_ca":true},{"name":"Martin Evans","is_ca":true},{"name":"Zenong Yin","is_ca":true},{"name":"Deborah Parra‐Medina","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0375605571900576,"gpt":0.4173247311766507,"spread":0.3797641739865931,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001339129,0.000614556,0.0004410236,0.0007730426,0.0004320701,0.001396236,0.001129925,0.0006406533,0.002865226],"category_scores_gemma":[0.002133535,0.0003552619,0.0004417361,0.0004923351,0.0001942195,0.001280152,0.001566537,0.0008000527,0.001007256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003527379,"about_ca_system_score_gemma":0.00114236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001256518,"about_ca_topic_score_gemma":0.001171569,"domain_scores_codex":[0.9987897,0.0002708681,0.0001330251,0.000242998,0.0003771359,0.0001864122],"domain_scores_gemma":[0.9987516,0.0003009208,0.0001122608,0.0002900992,0.0003405336,0.0002045462],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002298931,0.003117691,0.02966185,0.0008246905,0.0003199866,0.001542317,0.001098032,0.01139002,0.1218617,0.01396613,0.01919767,0.7947209],"study_design_scores_gemma":[0.0005636255,0.00337765,0.05150977,0.0005757153,0.0007032572,0.00197769,0.0009067272,0.4936879,0.2309517,0.01331425,0.2020734,0.000358403],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1287626,0.001007313,0.8224418,0.001371501,0.0006370762,0.002174925,0.0006496757,0.02775376,0.01520143],"genre_scores_gemma":[0.7109039,0.0007072099,0.2707533,0.0009288895,0.0001942023,0.0007273742,0.000887535,0.0005893586,0.01430829],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002865226,"threshold_uncertainty_score":0.009585142,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2730824771","doi":"10.2352/issn.2470-1173.2017.14.hvei-131","title":"Industry and business perspectives on the distinctions between visually lossless and lossy video quality: Mobile and large format displays","year":2017,"lang":"en","type":"article","venue":"Electronic Imaging","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Qualcomm (Canada); York University","funders":"","keywords":"Session (web analytics); Lossy compression; Lossless compression; Quality (philosophy); Computer science; Multimedia; Data compression; Computer vision; Artificial intelligence; World Wide Web","authors":[{"name":"Kjell Brunnström","is_ca":false},{"name":"Robert S. Allison","is_ca":true},{"name":"Damon M. Chandler","is_ca":false},{"name":"Hannah R. Colett","is_ca":false},{"name":"P. Corriveau","is_ca":false},{"name":"Scott Daly","is_ca":false},{"name":"James Goel","is_ca":true},{"name":"Jan Knopf","is_ca":false},{"name":"Laurie M. Wilcox","is_ca":true},{"name":"Yazilmiwati Yaacob","is_ca":false},{"name":"S. Yang","is_ca":false},{"name":"Ying Zhang","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02012784179695919,"gpt":0.3386129155165594,"spread":0.3184850737196002,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007791336,0.0005769185,0.0003882418,0.00208893,0.001487058,0.01107691,0.0008528965,0.004771815,0.007267517],"category_scores_gemma":[0.008963575,0.0002823117,0.0004233019,0.001545138,0.006592223,0.009415889,0.00296926,0.006053559,0.001151495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002757242,"about_ca_system_score_gemma":0.00136422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001807354,"about_ca_topic_score_gemma":0.002971188,"domain_scores_codex":[0.9959992,0.001298267,0.0001799045,0.0003569368,0.00184342,0.0003222276],"domain_scores_gemma":[0.9866236,0.007452284,0.001021344,0.0003184289,0.00379681,0.0007875464],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0003246928,0.0001408315,0.003020195,0.001402755,0.00002472776,0.001216825,0.007302535,0.0008035945,0.008346654,0.5784609,0.09068602,0.3082703],"study_design_scores_gemma":[0.00003911482,0.00047186,0.006279608,0.003320915,0.00004859527,0.002710146,0.02178114,0.001346211,0.005364302,0.1251744,0.8332918,0.0001719715],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.02356422,0.3822758,0.0231985,0.38119,0.006128346,0.00006121684,0.000133364,0.0001131465,0.1833354],"genre_scores_gemma":[0.5005711,0.3424065,0.01708344,0.07711722,0.017905,0.0001067407,0.0001487927,0.0001669169,0.0444943],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01107691,"threshold_uncertainty_score":0.04120505,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4322746013","doi":"10.2352/ei.2023.35.8.iqsp-302","title":"Age-specific perceptual image quality assessment","year":2023,"lang":"en","type":"article","venue":"Electronic Imaging","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Faurecia (Canada); McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Image quality; Metric (unit); Observer (physics); Artificial intelligence; Perception; Contrast (vision); Computer science; Image (mathematics); Visibility; Computer vision; Image contrast; Quality (philosophy); Quality Score; Pattern recognition (psychology); Psychology; Geography; Engineering","authors":[{"name":"Yinan Wang","is_ca":true},{"name":"Andrei Chubarau","is_ca":true},{"name":"Hyunjin Yoo","is_ca":true},{"name":"Tara Akhavan","is_ca":true},{"name":"James H. Clark","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04119883847731828,"gpt":0.3584759512656984,"spread":0.3172771127883801,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001211705,0.0005238928,0.0003624313,0.001004294,0.0001367243,0.0005229673,0.0004163442,0.0004831057,0.001217178],"category_scores_gemma":[0.004875455,0.0001703168,0.000610668,0.0004103992,0.0002190371,0.000878324,0.0005428743,0.000279578,0.0003330482],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000358343,"about_ca_system_score_gemma":0.0002479552,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002159483,"about_ca_topic_score_gemma":0.002348482,"domain_scores_codex":[0.9995611,0.00009989358,0.0000344888,0.0001233658,0.0001470734,0.00003412817],"domain_scores_gemma":[0.9981164,0.0004253417,0.0003532637,0.0002430851,0.0007699053,0.00009198445],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0007594132,0.0003825555,0.2886314,0.0004991854,0.0004625498,0.0004264631,0.0006441219,0.1472406,0.1688683,0.004463132,0.002210157,0.3854121],"study_design_scores_gemma":[0.00002506096,0.0009628354,0.2743057,0.00005388895,0.0002079463,0.001245703,0.0002133582,0.6485816,0.06608162,0.00496597,0.003230192,0.0001262192],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4819151,0.0009595449,0.5126581,0.00009608077,0.00004549359,0.000176717,0.0004997072,0.0007736551,0.002875625],"genre_scores_gemma":[0.9323059,0.0003260783,0.06609591,0.00004114599,0.00001663455,0.00006197939,0.0003025964,0.00004908363,0.0008006687],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002159483,"threshold_uncertainty_score":0.006408155,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4225433034","doi":"10.2352/ei.2022.34.1.vda-408","title":"AR visualization for coastal water navigation","year":2022,"lang":"en","type":"article","venue":"Electronic Imaging","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Dalhousie University","funders":"","keywords":"Visualization; Computer science; Human–computer interaction; Augmented reality; Officer; Subject matter; Data visualization; Real-time computing; Data mining; Geography","authors":[{"name":"Randy Herritt","is_ca":true},{"name":"Stephen Brooks","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01021178392041814,"gpt":0.3467075145057892,"spread":0.336495730585371,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006666861,0.000798022,0.0003038673,0.0007701325,0.0003530291,0.001508028,0.0007171616,0.0008656345,0.01888021],"category_scores_gemma":[0.002261542,0.0003399113,0.0004731331,0.0006899339,0.0003075472,0.0009215552,0.000988208,0.0007198447,0.00348536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003185321,"about_ca_system_score_gemma":0.0004166921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002028771,"about_ca_topic_score_gemma":0.002185777,"domain_scores_codex":[0.9995674,0.0001432072,0.00002445092,0.00005479946,0.0001840831,0.00002596182],"domain_scores_gemma":[0.9989023,0.0005014302,0.00006325836,0.0001720154,0.0002960101,0.00006492607],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006124414,0.0001730389,0.001503846,0.001057664,0.00007866922,0.0008656433,0.001464644,0.01323323,0.1557015,0.02328042,0.05406014,0.7479687],"study_design_scores_gemma":[0.0002594868,0.001267932,0.009404693,0.0009623803,0.000220395,0.004394985,0.000993774,0.1984493,0.08076625,0.0278322,0.6751619,0.0002866846],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0330637,0.01090394,0.8885756,0.001419744,0.0008313831,0.000198391,0.0009428832,0.01890378,0.04516075],"genre_scores_gemma":[0.3804939,0.01037184,0.5832884,0.0006293827,0.000433694,0.0003165969,0.001705178,0.001542908,0.02121818],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01888021,"threshold_uncertainty_score":0.0631606,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4399398838","doi":"10.2352/ei.2024.36.11.hvei-216","title":"Study on the Relationship Between Quality and Acceptability Annoyance (AccAnn) of UGC Videos","year":2024,"lang":"en","type":"article","venue":"Electronic Imaging","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Google (Canada)","funders":"","keywords":"Annoyance; Quality (philosophy); Computer science; Service quality; Applied psychology; Service (business); Psychology; Marketing; Business; Computer vision","authors":[{"name":"P. David","is_ca":false},{"name":"Pierre Lebreton","is_ca":false},{"name":"Neil Birkbeck","is_ca":true},{"name":"Yilin Wang","is_ca":true},{"name":"Balu Adsumilli","is_ca":false},{"name":"Patrick Le Callet","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0921170965318761,"gpt":0.4049013568267696,"spread":0.3127842602948935,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001279686,0.0005376311,0.0004167602,0.001287816,0.0002342131,0.0008381547,0.0002828848,0.0005016156,0.001153059],"category_scores_gemma":[0.01191285,0.0001020834,0.000441667,0.0008139702,0.0002339359,0.0007077456,0.0003579417,0.0007525377,0.0003862856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004269982,"about_ca_system_score_gemma":0.0002255169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007954466,"about_ca_topic_score_gemma":0.008880429,"domain_scores_codex":[0.9987373,0.0002104305,0.0001406543,0.000325144,0.0004673299,0.0001191983],"domain_scores_gemma":[0.9867938,0.007493218,0.002071702,0.0006368806,0.002556997,0.0004473923],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001219068,0.0005708917,0.835291,0.0006058105,0.0004616832,0.0004440304,0.0005473102,0.01012859,0.01247279,0.0003508435,0.004664731,0.1332433],"study_design_scores_gemma":[0.00001450654,0.0007608928,0.9161842,0.00004455477,0.00019073,0.0006922995,0.0005703698,0.07224537,0.006288238,0.0002671533,0.002675378,0.00006633179],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9863243,0.001138511,0.005818763,0.0001663943,0.00007020883,0.00006196155,0.004043567,0.0002038014,0.002172642],"genre_scores_gemma":[0.9916006,0.000309199,0.002495758,0.00003577017,0.00006166206,0.00003432695,0.00458326,0.00002360744,0.0008558841],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007954466,"threshold_uncertainty_score":0.01581633,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4399376051","doi":"10.2352/ei.2024.36.11.hvei-223","title":"Background- and Ambient-aware Image Visibility Enhancement for Transparent Displays","year":2024,"lang":"en","type":"article","venue":"Electronic Imaging","topic":"Advanced Optical Imaging Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Faurecia (Canada)","funders":"","keywords":"Visibility; Computer science; Computer vision; Image enhancement; Image (mathematics); Computer graphics (images); Artificial intelligence; Materials science; Optics; Physics","authors":[{"name":"Seungchul Ryu","is_ca":true},{"name":"Hyunjin Yoo","is_ca":true},{"name":"Tara Akhavan","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01375678064953682,"gpt":0.2859988205499428,"spread":0.272242039900406,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002139881,0.0005531557,0.0003288356,0.0005148791,0.0002719189,0.0006697946,0.0003822476,0.0003257018,0.000675237],"category_scores_gemma":[0.001031781,0.0001826327,0.0004066382,0.0003382097,0.0002712301,0.000750442,0.0005803021,0.0005162546,0.0002120481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002353265,"about_ca_system_score_gemma":0.000261414,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008990184,"about_ca_topic_score_gemma":0.0009505796,"domain_scores_codex":[0.9997528,0.00002785572,0.00001038199,0.00005082809,0.0001201359,0.0000380364],"domain_scores_gemma":[0.9995611,0.000106711,0.00008482047,0.00005380566,0.0001606546,0.00003291848],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004967629,0.00009425388,0.001834556,0.0002228638,0.00004994384,0.0002807993,0.0001887968,0.02134593,0.7632564,0.002738107,0.0008442416,0.2086474],"study_design_scores_gemma":[0.00003103552,0.0003925973,0.005028923,0.0000273841,0.00009651126,0.000707942,0.00006922449,0.431188,0.5556614,0.001160749,0.005589104,0.00004712986],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1669477,0.001054281,0.8284744,0.00007313324,0.00005570048,0.00003303057,0.00003774595,0.0010409,0.002283225],"genre_scores_gemma":[0.7808114,0.0009643603,0.2157182,0.00006897808,0.00005763428,0.00002430485,0.000130638,0.0001581323,0.002066338],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0008990184,"threshold_uncertainty_score":0.002258897,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4226474236","doi":"10.2352/ei.2022.34.1.vda-414","title":"Visualizing semantic 3D object clouds","year":2022,"lang":"en","type":"article","venue":"Electronic Imaging","topic":"3D Modeling in Geospatial Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Dalhousie University","funders":"","keywords":"Pairwise comparison; Computer science; Object (grammar); Consistency (knowledge bases); Similarity (geometry); Artificial intelligence; Semantic similarity; Set (abstract data type); Variety (cybernetics); Data mining; Image (mathematics)","authors":[{"name":"Bola Okesanjo","is_ca":true},{"name":"Stephen Brooks","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.004836166657297357,"gpt":0.2226281264234303,"spread":0.2177919597661329,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007479464,0.00102938,0.0007026403,0.003558926,0.0006314571,0.002523136,0.0009406942,0.00109428,0.00355796],"category_scores_gemma":[0.002692383,0.0005266932,0.001125773,0.00296148,0.0007494397,0.002099127,0.002211539,0.0008488605,0.0008159684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007727848,"about_ca_system_score_gemma":0.0008556234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00423422,"about_ca_topic_score_gemma":0.005423333,"domain_scores_codex":[0.9994979,0.00009397815,0.00002458023,0.00007704496,0.0002415632,0.0000650594],"domain_scores_gemma":[0.9991369,0.0002862166,0.00009250202,0.000152238,0.0002642957,0.00006791035],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004303344,0.0001610633,0.00673165,0.0007032676,0.0001989783,0.0009951629,0.001773329,0.5511119,0.05454781,0.1432902,0.01778071,0.2222755],"study_design_scores_gemma":[0.00004531265,0.00006061797,0.002348325,0.0001000949,0.00003128194,0.0004754899,0.0005616564,0.8908414,0.01803537,0.06763346,0.01979583,0.00007113298],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03102237,0.0003521635,0.9614744,0.0003351189,0.00007724851,0.0001083437,0.00120222,0.002250655,0.00317756],"genre_scores_gemma":[0.3712764,0.0008234395,0.6220152,0.0001505243,0.00007531489,0.0001411336,0.002870987,0.0008137937,0.001833131],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00423422,"threshold_uncertainty_score":0.01190251,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4295073990","doi":"10.2352/ei.2022.34.10.ipas-a10","title":"Image Processing: Algorithms and Systems XX Conference Overview and Papers Program","year":2022,"lang":"en","type":"article","venue":"Electronic Imaging","topic":"Image Processing Techniques and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Technische Universität München; Ames Research Center; York University; National Aeronautics and Space Administration","keywords":"Image processing; Computer science; Digital image processing; Algorithm; Image (mathematics); Artificial intelligence; Signal processing; Data science; Computer vision; Digital signal processing","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.01016990662218995,"gpt":0.2603541817413798,"spread":0.2501842751191898,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001975335,0.001468351,0.0008753414,0.003607862,0.0007255013,0.00453244,0.00115579,0.001876828,0.04958197],"category_scores_gemma":[0.002416397,0.000516076,0.0007123812,0.003902947,0.001019726,0.002950496,0.001579954,0.003326659,0.02833455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001324123,"about_ca_system_score_gemma":0.001927229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001364548,"about_ca_topic_score_gemma":0.00138802,"domain_scores_codex":[0.9986827,0.0002177326,0.00009678418,0.0002098638,0.0006984802,0.00009439622],"domain_scores_gemma":[0.9979271,0.0003367676,0.00007137706,0.0001816813,0.001282275,0.0002008208],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009099798,0.0001266084,0.0002760669,0.001244508,0.00004621335,0.00008150638,0.00007675619,0.002139379,0.00219997,0.03344124,0.399157,0.5611199],"study_design_scores_gemma":[0.00001090124,0.0001251338,0.0006326812,0.0005179317,0.00002722871,0.0003384193,0.00005496287,0.002992423,0.002145201,0.01026804,0.9828562,0.000030863],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"other","genre_scores_codex":[0.002857393,0.4557027,0.18527,0.01577033,0.04564106,0.0006731236,0.001432396,0.002254631,0.2903984],"genre_scores_gemma":[0.03186055,0.4510711,0.0905388,0.003222039,0.03768986,0.0006908108,0.003689436,0.001391726,0.3798457],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.04958197,"threshold_uncertainty_score":0.1658682,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2578926345","doi":"10.2352/issn.2470-1173.2016.15.ipas-184","title":"Image stitching by means of adaptive normalization","year":2016,"lang":"en","type":"article","venue":"Electronic Imaging","topic":"Image Processing Techniques and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; University of Waterloo","keywords":"Image stitching; Normalization (sociology); Artificial intelligence; Computer vision; Computer science; Pixel; Image processing; Filter (signal processing); Brightness; Image (mathematics); Pattern recognition (psychology); Optics","authors":[{"name":"Oleg Michailovich","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.003021460210378686,"gpt":0.20850620142495,"spread":0.2054847412145714,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006270559,0.0008873115,0.000732078,0.0009756283,0.0004339958,0.001062085,0.001007249,0.000873875,0.003525476],"category_scores_gemma":[0.001888388,0.0004158875,0.0009070543,0.001238021,0.0009900683,0.001145834,0.001098335,0.001159865,0.001748747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006182053,"about_ca_system_score_gemma":0.0008276235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001149286,"about_ca_topic_score_gemma":0.001646046,"domain_scores_codex":[0.9993731,0.00006834931,0.00004080678,0.0002038013,0.0002568205,0.00005700612],"domain_scores_gemma":[0.9991971,0.0001733314,0.0001032584,0.0002843153,0.000211537,0.00003046762],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002574796,0.0000774559,0.0006754288,0.0002189102,0.00008626832,0.0001928181,0.0002570768,0.04430339,0.4465155,0.02152035,0.002922161,0.4829732],"study_design_scores_gemma":[0.00001821927,0.0001508262,0.001489639,0.00002961394,0.00005033419,0.0005408814,0.00007746776,0.5932267,0.3749291,0.009102046,0.02030357,0.00008163379],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01097671,0.0001654453,0.9861271,0.00006802845,0.00006748225,0.00003508594,0.00005080117,0.0009313487,0.001578023],"genre_scores_gemma":[0.105533,0.0004614364,0.8876724,0.0001002995,0.00007686208,0.00009336972,0.0003135588,0.0004185971,0.00533052],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003525476,"threshold_uncertainty_score":0.01179385,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}