{"id":"W4242013611","doi":"10.1515/iupac.88.1219","title":"Postnatal","year":2017,"lang":"sv","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","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; Philosophy; Data mining","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001500686,0.001255747,0.001148871,0.003049243,0.0009862413,0.003308335,0.002372559,0.001568238,0.2468772],"category_scores_gemma":[0.01430919,0.0006015712,0.001410463,0.006299354,0.0003833691,0.002866057,0.002411487,0.001694911,0.2430729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001602164,"about_ca_system_score_gemma":0.002973124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0202327,"about_ca_topic_score_gemma":0.03083,"domain_scores_codex":[0.9975604,0.0003870186,0.000494408,0.000719132,0.0005720036,0.0002670411],"domain_scores_gemma":[0.9941472,0.00142538,0.0006581465,0.001329292,0.0021194,0.0003207206],"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":[0.00008507663,0.00001112719,0.001003549,0.0007533624,0.00001915215,0.00001518093,0.00002845194,0.00006282137,0.00005455034,0.0009027366,0.9892339,0.007830231],"study_design_scores_gemma":[0.0000843359,0.00001111713,0.00328887,0.0005660438,0.00001696176,0.00004795243,0.00008720258,0.00008011696,0.0001157585,0.001152315,0.9945315,0.00001764783],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001481425,0.0001294277,0.0001192902,0.0001778224,0.00006928957,0.00003208086,0.9945477,0.0002658231,0.004510529],"genre_scores_gemma":[0.0006282515,0.0001759365,0.0003474853,0.0002720585,0.00002643928,0.0001567756,0.9939295,0.0001237494,0.004339682],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7531227,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02020863578282483,"score_gpt":0.4565085746514498,"score_spread":0.436299938868625,"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."}}