{"id":"W7095613968","doi":"","title":"DEPARTEMENT DE BIOLOGIE FACULTÉ DES SCIENCES ET GÉNIE","year":2014,"lang":"en","type":"article","venue":"","topic":"Economic Growth and Productivity","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Selection (genetic algorithm); Perspective (graphical)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002180185,0.001203318,0.001661009,0.002719834,0.002205506,0.004374799,0.001701105,0.002635176,0.1620094],"category_scores_gemma":[0.008686278,0.0004698759,0.000753477,0.002116671,0.001457244,0.001591459,0.002627287,0.003961962,0.084494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007552407,"about_ca_system_score_gemma":0.009959463,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03874366,"about_ca_topic_score_gemma":0.0326375,"domain_scores_codex":[0.9973915,0.0003582275,0.0001170193,0.0008315864,0.0008335157,0.0004682771],"domain_scores_gemma":[0.9894748,0.002119701,0.0007527479,0.0007714418,0.002885198,0.003996055],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001648923,0.0005756691,0.04019831,0.001347827,0.000171297,0.001215813,0.002066696,0.001863967,0.007064131,0.07410537,0.4531834,0.4165586],"study_design_scores_gemma":[0.00008183072,0.0001769718,0.05427602,0.0002710235,0.00002365326,0.0007107118,0.0005930738,0.0009546943,0.003746124,0.007518237,0.9315714,0.00007626035],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.07534873,0.08172106,0.02481619,0.1520798,0.02444999,0.0006985368,0.04011935,0.00561594,0.5951505],"genre_scores_gemma":[0.1284936,0.0198052,0.01484788,0.003372299,0.002926469,0.000272472,0.006135127,0.0005379872,0.8236089],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.8379906,"threshold_uncertainty_score":0.5419754,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1620443216057343,"score_gpt":0.2934273325360188,"score_spread":0.1313830109302845,"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."}}