{"id":"W2982447037","doi":"10.3138/9781487579425","title":"Canadian Selection Filmstrips","year":2023,"lang":"en","type":"article","venue":"Project Muse (Johns Hopkins University)","topic":"Hermeneutics and Narrative Identity","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Selection (genetic algorithm); Computer science; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000610764,0.001175552,0.0005394894,0.01065283,0.01009328,0.004711831,0.001428331,0.0005727448,0.3370628],"category_scores_gemma":[0.002757596,0.0004903965,0.0004183109,0.01988295,0.0007788185,0.001189278,0.001611543,0.001239629,0.05149414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01516586,"about_ca_system_score_gemma":0.02203102,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8161026,"about_ca_topic_score_gemma":0.9359592,"domain_scores_codex":[0.9987388,0.00005941964,0.00003399593,0.0001337916,0.0008096301,0.0002243117],"domain_scores_gemma":[0.997239,0.0001633095,0.00005850211,0.0001219861,0.002069844,0.0003474046],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003103368,0.000006442791,0.0002185249,0.0001680408,0.000002871087,0.0001431383,0.001165479,0.00003625721,0.0004270557,0.003188071,0.9539341,0.04067887],"study_design_scores_gemma":[0.000001439633,0.000002110188,0.001073371,0.00006826491,0.000001963813,0.00004155037,0.0006194761,0.00001168302,0.0001048596,0.00007440678,0.9979954,0.000005598083],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.005065486,0.005037172,0.0005259105,0.00157303,0.002647432,0.0002183341,0.03316538,0.0006900415,0.9510772],"genre_scores_gemma":[0.02060615,0.008360006,0.001897822,0.0007031162,0.0004399683,0.0001722311,0.02596664,0.0008346754,0.9410195],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3370628,"threshold_uncertainty_score":0.9455995,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0304992447852538,"score_gpt":0.2143300545614112,"score_spread":0.1838308097761574,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}