{"id":"W6917366952","doi":"10.57745/1055dq","title":"GlycemicExcursions_+8h of recovery.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":"Identification (biology); Product (mathematics); Process (computing)","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":[0.0008537263,0.003629432,0.002040467,0.00279352,0.0008316993,0.002755579,0.002969581,0.003597573,0.1336821],"category_scores_gemma":[0.004872501,0.0008862401,0.002061958,0.004281671,0.0004680202,0.001507415,0.001603682,0.001838013,0.1619414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002002069,"about_ca_system_score_gemma":0.002374198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04359045,"about_ca_topic_score_gemma":0.05974672,"domain_scores_codex":[0.9991068,0.0001344196,0.00007494519,0.0003245315,0.0001709985,0.0001882742],"domain_scores_gemma":[0.9982492,0.000515387,0.0001410217,0.000480045,0.0004216155,0.0001927659],"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":[0.0001052933,0.00002004518,0.0003356297,0.0003659528,0.00002317555,0.00001107249,0.00000811954,0.000240679,0.00007204591,0.0001965673,0.9968732,0.001748331],"study_design_scores_gemma":[0.0007649481,0.0000702668,0.004492495,0.0004260105,0.00005399976,0.0000936817,0.00007776899,0.001151655,0.0006843542,0.001716804,0.9904033,0.00006469875],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001297694,0.0001102493,0.00004622765,0.00008210126,0.0000429269,0.000008058138,0.9981053,0.0007707938,0.0007044276],"genre_scores_gemma":[0.0005478759,0.00008896628,0.0002340853,0.00009372833,0.00001827423,0.00003350613,0.9978654,0.0001801635,0.0009379983],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8663179,"threshold_uncertainty_score":0.4472111,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4085897146495174,"score_gpt":0.4470449539022857,"score_spread":0.03845523925276828,"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."}}