{"id":"W6907595737","doi":"10.25318/1310049601-fra","title":"Allaitement","year":2019,"lang":"fr","type":"dataset","venue":"Statistics Canada Dissemination","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"MEDLINE; Product (mathematics); Identification (biology)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004894008,0.0009256267,0.000774972,0.0003010232,0.0002725147,0.0002229822,0.0007780402,0.0003958131,0.007668436],"category_scores_gemma":[0.001375097,0.001160156,0.00005459498,0.000596969,0.00014792,0.0001543087,0.0002007455,0.0007143186,0.008281432],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006841778,"about_ca_system_score_gemma":0.00346194,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5825624,"about_ca_topic_score_gemma":0.9820706,"domain_scores_codex":[0.9938284,0.0003072587,0.00115579,0.001000034,0.002661263,0.001047283],"domain_scores_gemma":[0.99478,0.001307451,0.001174684,0.001249202,0.001011117,0.000477525],"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":[0.00003414303,0.0001843358,0.00005312732,0.001479313,0.0002407067,0.000314831,0.00005070132,0.0002480763,0.0001044266,0.004572161,0.987883,0.004835224],"study_design_scores_gemma":[0.0003437407,0.0001249921,0.007493583,0.0007178837,0.0006490944,0.00001784313,0.0002294056,0.001432655,0.00009371254,0.0001229288,0.9875903,0.001183898],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003084207,0.0006220544,0.002163001,0.00029414,0.005981258,0.001176306,0.9894525,0.00002131597,0.0002585825],"genre_scores_gemma":[0.0003339055,0.0002224731,0.002488606,0.000211392,0.0003242198,0.00008700932,0.9807705,0.0002246711,0.01533718],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3995082,"threshold_uncertainty_score":0.9990848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01020757679618846,"score_gpt":0.2813301643115658,"score_spread":0.2711225875153773,"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."}}