{"id":"W4392775866","doi":"10.3917/dm.043.0207","title":"Calibration internationale des échelles sémantiques","year":2006,"lang":"fr","type":"article","venue":"Décisions Marketing","topic":"Sensory Analysis and Statistical Methods","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Humanities; Political science; Art","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001785295,0.0001704471,0.0002170737,0.00003345441,0.0005463383,0.0002328434,0.0001880624,0.0001367946,0.007644746],"category_scores_gemma":[0.0021743,0.00008532277,0.0001754709,0.000434227,0.0002489196,0.0002157654,0.0000870637,0.000150009,0.00007281479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004205251,"about_ca_system_score_gemma":0.000008838267,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001729055,"about_ca_topic_score_gemma":0.0008866119,"domain_scores_codex":[0.9973983,0.001210663,0.0004618986,0.0003520974,0.0002578098,0.0003192009],"domain_scores_gemma":[0.9950172,0.004533383,0.0001403573,0.00006502789,0.0001540273,0.00009000791],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0000593449,0.0002589673,0.03166636,0.0000319571,0.00003575695,0.00002557295,0.00004200759,0.0002361976,0.02300799,0.05710345,0.01312865,0.8744037],"study_design_scores_gemma":[0.0001613974,0.000117557,0.6506895,0.0004580941,0.0001100562,0.00002291341,0.0006021048,0.0706055,0.00269333,0.08361774,0.1904155,0.0005063319],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9223226,0.007814539,0.02125848,0.007350981,0.0005242227,0.0001436147,0.0001410625,0.00008042706,0.04036409],"genre_scores_gemma":[0.7744769,0.001070317,0.09285291,0.0002735074,0.001821493,0.00001129835,0.0001876172,0.000005243605,0.1293007],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8738974,"threshold_uncertainty_score":0.9932624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04580734846864752,"score_gpt":0.297136881228545,"score_spread":0.2513295327598975,"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."}}