{"id":"W4252229116","doi":"10.1515/iupac.88.1207","title":"Pleiotropism","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Morphological variations and asymmetry","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Relation (database); Computer science; Linguistics; Data mining; Philosophy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001050699,0.001849184,0.001419065,0.004080311,0.0009811457,0.003281022,0.002265729,0.001546606,0.1085888],"category_scores_gemma":[0.009589433,0.0006806371,0.001892437,0.005820981,0.0005513555,0.002179385,0.002481402,0.001812837,0.09934629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001169853,"about_ca_system_score_gemma":0.001903811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01127068,"about_ca_topic_score_gemma":0.02419333,"domain_scores_codex":[0.9985837,0.000199072,0.0002506185,0.0005000093,0.0003082173,0.0001584849],"domain_scores_gemma":[0.9968258,0.001115667,0.000438359,0.0008871901,0.0005579239,0.0001750685],"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":[0.0001410839,0.00002066864,0.00369035,0.002224919,0.00006583489,0.00005606774,0.00004295961,0.0003781376,0.0002751226,0.00179317,0.9799834,0.01132835],"study_design_scores_gemma":[0.0001365156,0.00001650765,0.009167947,0.0007431899,0.00004597227,0.0001992178,0.00007290583,0.0003180332,0.000295127,0.002640765,0.9863266,0.00003734319],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003026166,0.0003143182,0.0002645202,0.00008988215,0.00005702289,0.0000183147,0.9961638,0.000543343,0.002246113],"genre_scores_gemma":[0.00113148,0.0003137166,0.0008409264,0.0001169482,0.00001807314,0.0001246554,0.9959795,0.0001617556,0.00131278],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1085888,"threshold_uncertainty_score":0.3632658,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04957752722027601,"score_gpt":0.4639182423805034,"score_spread":0.4143407151602274,"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."}}