{"id":"W2999486412","doi":"","title":"Identification des informations sensibles dans des sources de données hétérogènes","year":2019,"lang":"fr","type":"article","venue":"Archipelago (Université du Québec à Montréal)","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Political science; Humanities; Philosophy","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","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002183396,0.0003464864,0.0004036717,0.0006334928,0.001850533,0.0006896986,0.001489074,0.0001508469,0.0009400469],"category_scores_gemma":[0.0005569482,0.0003551074,0.000294022,0.001106967,0.001515613,0.003592814,0.0009113672,0.0002567568,0.003847493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005521632,"about_ca_system_score_gemma":0.0004518416,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.3905186,"about_ca_topic_score_gemma":0.7354709,"domain_scores_codex":[0.996473,0.0005808702,0.0007459203,0.0005936552,0.0008846997,0.0007218333],"domain_scores_gemma":[0.9966141,0.001111759,0.0004697547,0.001123339,0.0003298211,0.0003512014],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00008561582,0.0003117867,0.04071537,0.0003294993,0.0002415085,0.00005807964,0.5521218,0.003410968,0.002763886,0.108819,0.005666704,0.2854759],"study_design_scores_gemma":[0.0009726112,0.0001900496,0.1764987,0.0002792465,0.000273091,0.00009008586,0.6047454,0.01065767,0.0007155053,0.0691293,0.1357992,0.0006491421],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.949199,0.004874891,0.03307194,0.005898915,0.0004096824,0.0004501809,0.0001732673,0.0001362091,0.005785881],"genre_scores_gemma":[0.9746218,0.001783118,0.00241173,0.0002994458,0.00008672393,0.000006169877,0.00005549808,0.00002557474,0.02070998],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3449523,"threshold_uncertainty_score":0.9999732,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02994404405101326,"score_gpt":0.2398146214254995,"score_spread":0.2098705773744863,"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."}}