{"id":"W7068859793","doi":"","title":"FOQ Canada","year":2005,"lang":"en","type":"article","venue":"Érudit (Université de Montréal)","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Nucleofection; Gestational period; TSG101; Dysgeusia; Liquation; Diafiltration; Emperipolesis; Triacetin; Demotion","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":[0.000297238,0.0001423468,0.0001654618,0.00005140045,0.0004654498,0.00003361368,0.0005449469,0.0000509594,0.002541724],"category_scores_gemma":[0.0000603775,0.0001459487,0.00003686843,0.0001528073,0.00006352193,0.0002028325,0.0002612641,0.0000904518,0.000586232],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005454973,"about_ca_system_score_gemma":0.0001784602,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6350397,"about_ca_topic_score_gemma":0.9672868,"domain_scores_codex":[0.9986462,0.00008041189,0.0001349172,0.0003219382,0.0003707527,0.0004457831],"domain_scores_gemma":[0.9992581,0.00005844985,0.0001087676,0.0003450487,0.00004539405,0.0001842311],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008187211,0.00004262709,0.001376511,0.00002805474,0.00001075649,0.0007555273,0.0003160295,0.02059451,0.65865,0.008348661,0.2986781,0.0111173],"study_design_scores_gemma":[0.0002834346,0.00002449041,0.001860991,0.000008741605,0.00001605716,0.000177399,0.00006550466,0.00398528,0.02896562,0.00009818613,0.9642915,0.0002228346],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9727721,0.001190416,0.0005104811,0.01871584,0.0003989793,0.00009636788,0.00002571266,0.0001546788,0.006135473],"genre_scores_gemma":[0.9605702,0.00009786025,0.0102825,0.001110895,0.0002254011,0.000003595865,0.000006317429,0.00002223586,0.02768099],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6656134,"threshold_uncertainty_score":0.9983701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002788843700754576,"score_gpt":0.1510032861681296,"score_spread":0.1482144424673751,"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."}}