{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","open_science","research_integrity","insufficient_payload"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.008510536,0.001088568,0.001791702,0.0008103048,0.0001431964,0.000102425,0.01068856,0.003030675,0.000503247],"category_scores_gemma":[0.01922987,0.001149473,0.0002827629,0.004228453,0.0004703253,0.0009140473,0.004004922,0.004900745,0.1256323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008085591,"about_ca_system_score_gemma":0.001363837,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008350194,"about_ca_topic_score_gemma":0.00165091,"domain_scores_codex":[0.9910679,0.002118169,0.001580007,0.00259998,0.001443299,0.001190683],"domain_scores_gemma":[0.9782497,0.004221683,0.001572419,0.01524704,0.0004009179,0.0003082265],"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":[0.0002675134,0.0002716032,0.000008558551,0.0009099492,0.0003778476,0.00006022161,0.00001945372,0.00001986585,0.0004815193,0.000003316461,0.9937184,0.003861764],"study_design_scores_gemma":[0.0008448657,0.0001097922,0.00007141662,0.001403197,0.0004455786,0.00002563949,0.00004365812,0.0001159259,0.0002075646,0.0003609356,0.9952789,0.001092524],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003941931,0.002872022,0.0000779776,0.0001551183,0.002312246,0.0008983111,0.9929484,0.0004502273,0.0002462557],"genre_scores_gemma":[4.651191e-7,0.01191974,0.005918386,0.0001639329,0.0009275666,0.00009594119,0.9765123,0.000428405,0.00403327],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.125129,"threshold_uncertainty_score":0.9990956,"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."}}