{"id":"W7132575376","doi":"","title":"I Relazione tecnica descrittiva delle attività svolte nell'ambito dell'Accordo di collaborazione triennale MATTM-DGSVI e CNR-IIA","year":2019,"lang":"it","type":"other","venue":"CNR ExploRA","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Population; Citizenship; Regional development","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","sts","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"category_scores_codex":[0.003762635,0.006393439,0.007479369,0.003079727,0.001830839,0.001604837,0.005715439,0.005201781,0.0176461],"category_scores_gemma":[0.001696246,0.006961212,0.002420864,0.009658116,0.002697278,0.00262245,0.003460833,0.005253404,0.4786103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003409927,"about_ca_system_score_gemma":0.003700402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006337262,"about_ca_topic_score_gemma":0.0003989814,"domain_scores_codex":[0.972483,0.003312903,0.005125825,0.007765566,0.004756452,0.006556239],"domain_scores_gemma":[0.9769287,0.001837856,0.005026349,0.01075512,0.002502817,0.002949205],"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":[0.004650312,0.004731032,0.002783769,0.001864393,0.002939033,0.001314344,0.003750533,0.0004616774,0.03239824,0.001580215,0.9398822,0.003644229],"study_design_scores_gemma":[0.01123806,0.001779981,0.0005360207,0.005789386,0.002170573,0.0002689358,0.005217307,0.0009037578,0.005439255,0.000587928,0.9582646,0.007804202],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.07617456,0.1191075,0.01826192,0.007443455,0.04007031,0.0415399,0.02455202,0.01194965,0.6609007],"genre_scores_gemma":[0.08599834,0.01339386,0.004786204,0.00102134,0.005961207,0.00202016,0.003346116,0.0148869,0.8685859],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4609642,"threshold_uncertainty_score":0.9996641,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03275796054170169,"score_gpt":0.2556961784840708,"score_spread":0.2229382179423691,"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."}}