{"id":"W6996783321","doi":"","title":"Tests de lisibilité des notices patient dans l'industrie pharmaceutique (aspects réglementaires, contraintes et opportunités)","year":2010,"lang":"fr","type":"other","venue":"OpenGrey (Institut de l'Information Scientifique et Technique)","topic":"Additive Manufacturing Materials and Processes","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Notice; Vetting; Context (archaeology)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01025005,0.0007361535,0.0006469396,0.003691525,0.001219433,0.00351909,0.000981992,0.001919587,0.02179687],"category_scores_gemma":[0.0286399,0.0003964864,0.0009683984,0.002552514,0.001352978,0.001686668,0.001268642,0.001509109,0.006680325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002311264,"about_ca_system_score_gemma":0.004651596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007413926,"about_ca_topic_score_gemma":0.01053267,"domain_scores_codex":[0.9860887,0.003727542,0.001567142,0.0006958119,0.007135137,0.0007857335],"domain_scores_gemma":[0.9595946,0.01864079,0.008922003,0.001813657,0.009926637,0.001102248],"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":[0.004356477,0.001622049,0.1309516,0.008538227,0.0002897085,0.00300601,0.01092051,0.0008245082,0.1557097,0.00909147,0.09751946,0.5771703],"study_design_scores_gemma":[0.0001650378,0.003670569,0.1722903,0.002031266,0.0003373751,0.003790917,0.006432496,0.0008853878,0.2250997,0.002723819,0.5822061,0.0003669685],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.6106504,0.05009748,0.04708203,0.02947066,0.004725064,0.00418758,0.02468608,0.005045589,0.2240551],"genre_scores_gemma":[0.6576046,0.03495092,0.08366464,0.008243302,0.0009740324,0.002072878,0.01358536,0.0008641036,0.1980401],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.02179687,"threshold_uncertainty_score":0.07291782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03085749654023797,"score_gpt":0.2894069180103011,"score_spread":0.2585494214700631,"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."}}