{"id":"W2766649693","doi":"10.3917/sava.041.0017","title":"Perturbateurs d’intérêts","year":2017,"lang":"fr","type":"article","venue":"Savoir/Agir","topic":"Social Sciences and Governance","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"World Federation of Science Journalists","funders":"","keywords":"INT; Computer science; Programming language","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00473978,0.002833401,0.002118569,0.004507505,0.004294123,0.007322412,0.001884375,0.003773076,0.02353839],"category_scores_gemma":[0.02334291,0.001139453,0.002912776,0.001713341,0.006253853,0.005062022,0.005343451,0.007886928,0.004656721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006479865,"about_ca_system_score_gemma":0.001662534,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01218932,"about_ca_topic_score_gemma":0.007083629,"domain_scores_codex":[0.993529,0.002441559,0.0001824123,0.001269341,0.002010487,0.0005672113],"domain_scores_gemma":[0.9890423,0.005419489,0.0008770433,0.001599215,0.001634604,0.001427268],"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":[0.0004478317,0.00013343,0.001772796,0.0001451751,0.0002289501,0.0006206198,0.0006956441,0.02219001,0.008108798,0.9389459,0.00460499,0.02210582],"study_design_scores_gemma":[0.0006185835,0.0004037435,0.007727222,0.0001078981,0.0001208028,0.001525211,0.001892859,0.2076028,0.00939077,0.6942762,0.07614791,0.0001862156],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2955047,0.002492023,0.4591964,0.007076408,0.003027508,0.0003511165,0.000893736,0.002097701,0.2293603],"genre_scores_gemma":[0.8067576,0.001813103,0.04439317,0.0009485206,0.001775997,0.0005898179,0.0007933058,0.0008930604,0.1420354],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02353839,"threshold_uncertainty_score":0.07874376,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0815272250350046,"score_gpt":0.3477265535004411,"score_spread":0.2661993284654365,"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."}}