{"id":"W6889007441","doi":"10.24443/usi-arc-bib_fcor.2735","title":"Montréal","year":2022,"lang":"fr","type":"other","venue":"USI-Biblioteca","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Process (computing); Identification (biology); Product (mathematics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","bibliometrics","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","bibliometrics","research_integrity","insufficient_payload"],"category_scores_codex":[0.001034473,0.001683814,0.00156641,0.02501637,0.000702374,0.0005399153,0.002201567,0.001605685,0.8555986],"category_scores_gemma":[0.0003795956,0.001963503,0.0008812728,0.02864143,0.0005705914,0.0003660747,0.001991495,0.003280947,0.4137444],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002159747,"about_ca_system_score_gemma":0.0007416455,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0110175,"about_ca_topic_score_gemma":0.006436102,"domain_scores_codex":[0.9915921,0.0008919613,0.001038848,0.00204684,0.002314775,0.002115458],"domain_scores_gemma":[0.9948682,0.0002811853,0.0009949325,0.002921825,0.0001727939,0.000761116],"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":[0.0001446589,0.0006675304,0.0007202679,0.0002501089,0.0006851259,0.001088908,0.0004372978,0.0005692679,0.001400939,0.0107582,0.9691277,0.01415006],"study_design_scores_gemma":[0.001616941,0.0003192949,0.001863113,0.000224751,0.0004964468,0.000267087,0.0001928395,0.0007518407,0.000118736,0.00060615,0.9915464,0.001996411],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0007769038,0.07625677,0.0001212274,0.002115619,0.004584112,0.001529345,0.003072764,0.001141625,0.9104016],"genre_scores_gemma":[0.0008709724,0.004043758,0.001833702,0.001287001,0.003505647,0.0002831215,0.0005901178,0.005345558,0.9822401],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4418542,"threshold_uncertainty_score":0.9996904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0105238824413282,"score_gpt":0.224283663495869,"score_spread":0.2137597810545408,"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."}}