{"id":"W2604855839","doi":"10.71781/8750","title":"Le Commissariat général à l'information comme agent de renforcement du moral français","year":2006,"lang":"fr","type":"dissertation","venue":"Open MIND","topic":"European Criminal Justice and Data Protection","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Humanities; Political science; Library science; Philosophy; Computer science","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","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001252213,0.0003117103,0.0003392084,0.0001133268,0.001556304,0.001040323,0.001003117,0.0003189741,0.002652947],"category_scores_gemma":[0.0001141112,0.0003641721,0.000134026,0.0003003129,0.0001678266,0.002288508,0.0002047572,0.0004172083,0.00408394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002887202,"about_ca_system_score_gemma":0.0006200815,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1766385,"about_ca_topic_score_gemma":0.0350911,"domain_scores_codex":[0.9975437,0.0003952719,0.0007050019,0.0003197509,0.0005253256,0.0005109634],"domain_scores_gemma":[0.9986383,0.0000673485,0.0005652112,0.0003276015,0.0002084578,0.0001931031],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008177527,0.000789465,0.001979723,0.0005092007,0.0001934848,0.00007040238,0.277387,0.002077222,0.000385042,0.03911769,0.04401718,0.6326559],"study_design_scores_gemma":[0.0008985676,0.0002332258,0.00464438,0.0002795329,0.0004019761,0.000006412244,0.07345273,0.001768797,0.001165352,0.0002215104,0.9163638,0.0005637162],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2313312,0.0001661589,0.003932555,0.001985734,0.001943519,0.001755381,0.0002894644,0.00001017956,0.7585858],"genre_scores_gemma":[0.9566854,0.0002152679,0.005521778,0.0004748704,0.0008344715,0.00008477807,0.01127794,0.00003938936,0.02486617],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8723466,"threshold_uncertainty_score":0.9999967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07404274291479003,"score_gpt":0.3274491402961643,"score_spread":0.2534063973813743,"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."}}