{"id":"W6898734530","doi":"10.57745/mzd1ky","title":"GlycemicExcursions_night.tab","year":2023,"lang":"en","type":"dataset","venue":"Recherche Data Gouv France","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Process (computing); Identification (biology); Product (mathematics)","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":[0.0009145627,0.003837887,0.001983855,0.003491525,0.0007672302,0.003239506,0.00303627,0.003596641,0.1527057],"category_scores_gemma":[0.005208164,0.001031042,0.001950242,0.005727971,0.000486282,0.001582063,0.001692185,0.001949369,0.1844211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002169268,"about_ca_system_score_gemma":0.00244466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04395922,"about_ca_topic_score_gemma":0.05380927,"domain_scores_codex":[0.9991246,0.0001356968,0.00008017234,0.0002998129,0.0001810416,0.0001786676],"domain_scores_gemma":[0.9979062,0.0006562324,0.0001787952,0.0005285582,0.0004903605,0.0002398482],"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":[0.00008484266,0.00001856593,0.0002974186,0.0003767961,0.00002547766,0.00001216236,0.00001048399,0.0002044785,0.00007691329,0.0002075814,0.9972619,0.001423359],"study_design_scores_gemma":[0.0006666455,0.00004834632,0.003990312,0.0003603479,0.00004592177,0.00007896403,0.0000611984,0.0008589361,0.0006059127,0.001412647,0.991811,0.00005956171],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008873695,0.00007046937,0.00003663046,0.00007345244,0.00002931558,0.000006710541,0.9984114,0.0006751386,0.0006080589],"genre_scores_gemma":[0.0004135542,0.00007273177,0.0001649257,0.00007948354,0.0000141328,0.00003442279,0.9982744,0.0001874022,0.0007589312],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8472943,"threshold_uncertainty_score":0.5108513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4926668887896364,"score_gpt":0.4674222688741104,"score_spread":0.02524461991552601,"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."}}