{"id":"W4398875507","doi":"10.7910/dvn/tlahpx/occfad","title":"ddAle_Ott_20140929_11107000.mat","year":2020,"lang":"fr","type":"dataset","venue":"Harvard Dataverse","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Computer science","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":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"category_scores_codex":[0.001069011,0.002495051,0.00240959,0.0007067508,0.0005757355,0.0009089615,0.005191023,0.001752937,0.1887222],"category_scores_gemma":[0.002501409,0.002912088,0.0008944244,0.001546841,0.00139195,0.001846249,0.004695886,0.003138403,0.9993758],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001190851,"about_ca_system_score_gemma":0.001058062,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001009277,"about_ca_topic_score_gemma":0.0006417438,"domain_scores_codex":[0.9888154,0.001252437,0.001889923,0.003331274,0.002217817,0.002493096],"domain_scores_gemma":[0.988086,0.0004875638,0.00150753,0.007202609,0.0003668036,0.002349536],"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":[0.0005564129,0.000746083,0.00003379597,0.001632626,0.001025407,0.004237164,0.0001466422,0.00003753765,0.0006821225,0.001011472,0.9892302,0.0006604922],"study_design_scores_gemma":[0.002582544,0.0003314337,0.0000618858,0.0008499136,0.002239409,0.0003790969,0.0002296038,0.0004736694,0.0001648417,0.0000562402,0.9897895,0.002841855],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001547388,0.00001060198,0.00009168527,0.00009220878,0.005909436,0.001563346,0.9879289,0.0005994026,0.00378895],"genre_scores_gemma":[0.00001123405,0.001357686,0.002238075,0.002884829,0.003908888,0.0001235398,0.9829397,0.0008371106,0.005698896],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8106536,"threshold_uncertainty_score":0.999543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02430225019971765,"score_gpt":0.2489469377863906,"score_spread":0.2246446875866729,"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."}}