{"id":"W6950559328","doi":"10.5281/zenodo.7994922","title":"Mir@bel : nos données s'affichent chez vous","year":2023,"lang":"fr","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Cultural Insights and Digital Impacts","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bell (Canada)","funders":"","keywords":"Product (mathematics); Context (archaeology); Presentation (obstetrics)","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":[],"consensus_categories":[],"category_scores_codex":[0.008374951,0.00182096,0.001726513,0.008305446,0.002871659,0.01389302,0.002962147,0.003484888,0.08459513],"category_scores_gemma":[0.04346745,0.001792145,0.002365549,0.007457138,0.002138409,0.01560177,0.00867777,0.004408052,0.06859905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002962494,"about_ca_system_score_gemma":0.005947525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02808064,"about_ca_topic_score_gemma":0.04149722,"domain_scores_codex":[0.9895943,0.001818745,0.001202202,0.001207721,0.005711892,0.0004650142],"domain_scores_gemma":[0.9803892,0.00673533,0.0005962879,0.005749562,0.006008805,0.000520776],"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":[0.001212966,0.0001310837,0.003706139,0.005196226,0.0002613851,0.0009386493,0.006265529,0.001592997,0.01168131,0.07313182,0.6194389,0.2764429],"study_design_scores_gemma":[0.00002461454,0.0000164204,0.0009363027,0.0006664247,0.00004111842,0.0002561335,0.0005439452,0.0009214175,0.002373388,0.004896522,0.9892588,0.00006489498],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0149137,0.01631466,0.314784,0.01928958,0.004548742,0.000634329,0.1460035,0.1928203,0.2906911],"genre_scores_gemma":[0.1137826,0.01790143,0.2758501,0.008365646,0.001231199,0.00136562,0.2817556,0.0975342,0.2022137],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08459513,"threshold_uncertainty_score":0.2829989,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.253866787295302,"score_gpt":0.2895423528679534,"score_spread":0.03567556557265145,"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."}}