{"id":"W6898780764","doi":"10.57745/fyxwjz","title":"Up to 10 days of recovery.tab","year":2024,"lang":"en","type":"dataset","venue":"Recherche Data Gouv France","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Clinical Research Institute","funders":"","keywords":"Continuous glucose monitoring; Key (lock); Data collection; Component (thermodynamics)","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":[0.0008111978,0.002087644,0.001572356,0.001823721,0.0006116874,0.001765728,0.001437321,0.002013119,0.07219396],"category_scores_gemma":[0.003866283,0.000579625,0.001527819,0.002681662,0.0003211107,0.001030513,0.00108254,0.001510293,0.07850242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001258127,"about_ca_system_score_gemma":0.00158378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02217641,"about_ca_topic_score_gemma":0.03140925,"domain_scores_codex":[0.9992597,0.00009011592,0.00009681424,0.0002810814,0.0001436394,0.0001286932],"domain_scores_gemma":[0.9982242,0.0005084278,0.0001542039,0.0004718103,0.0005003802,0.0001409742],"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":[0.0002541129,0.00003473493,0.001256131,0.000452553,0.00004142326,0.00003469272,0.00001278042,0.0002650582,0.0002877166,0.0001860171,0.9933515,0.003823301],"study_design_scores_gemma":[0.0005832586,0.00008722839,0.01634265,0.0004386586,0.00008038554,0.0002021166,0.00007781923,0.0007733526,0.001495253,0.001301959,0.9785475,0.00006980914],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001892819,0.00006615267,0.00004117793,0.00005261345,0.0000353567,0.000007565568,0.9988396,0.0003189389,0.0004493541],"genre_scores_gemma":[0.0006540627,0.00005305757,0.0001665904,0.00005847079,0.00001041439,0.00002948759,0.9983025,0.00007325772,0.000652115],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.927806,"threshold_uncertainty_score":0.2415128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3247767036851163,"score_gpt":0.440083758883755,"score_spread":0.1153070551986387,"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."}}