{"id":"W2117344595","doi":"10.7202/001331ar","title":"Apparaître et leurrer","year":2009,"lang":"fr","type":"article","venue":"Protée","topic":"Cultural Insights and Digital Impacts","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Humanities; Art","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001208015,0.0001958435,0.0001651991,0.00003530164,0.00009004174,0.001583474,0.0003737488,0.00009156645,0.0001063597],"category_scores_gemma":[0.00005265297,0.0001453317,0.00009705182,0.0003079012,0.00006282296,0.003322392,0.0001110525,0.0001955002,0.001131639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003332109,"about_ca_system_score_gemma":0.0000930415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001202855,"about_ca_topic_score_gemma":0.00001644527,"domain_scores_codex":[0.9987534,0.00004911197,0.0001937696,0.0003402737,0.0002333983,0.0004300975],"domain_scores_gemma":[0.9992036,0.00002410936,0.00006574913,0.0003582364,0.0001060581,0.0002422357],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000005662167,0.000213073,0.00002435318,0.00001833473,0.000007673287,0.0001263956,0.002088712,0.00003258137,0.0004195808,0.7111804,0.05990047,0.2259827],"study_design_scores_gemma":[0.0003006897,0.0004181635,0.004654535,0.0001455111,0.000008316727,0.0002667975,0.00001726458,0.002242228,0.002724938,0.1017273,0.8871378,0.0003564587],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.007379944,0.0138423,0.01332238,0.1391811,0.001775446,0.000795006,0.00001126413,0.0002639704,0.8234285],"genre_scores_gemma":[0.7118363,0.0001521246,0.005372216,0.01740826,0.0004921841,0.00001343039,0.00000701505,0.00001160635,0.2647069],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.8272373,"threshold_uncertainty_score":0.9996461,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3859023607981363,"score_gpt":0.3638025445800481,"score_spread":0.02209981621808826,"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."}}