{"id":"W3206170720","doi":"10.3390/books978-3-03928-665-2","title":"Claim Models","year":2020,"lang":"en","type":"book","venue":"","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Computer science; Artificial intelligence; Machine learning; Artificial neural network; Boosting (machine learning); Construct (python library)","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001402262,0.000275947,0.0006549027,0.0001623572,0.0001061288,0.00026756,0.001824464,0.0004976373,0.003655437],"category_scores_gemma":[0.0004974375,0.0001712594,0.0004055294,0.0001879505,0.0001628031,0.000363368,0.0004921491,0.0005424877,0.01017995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000955543,"about_ca_system_score_gemma":0.0008506408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006137161,"about_ca_topic_score_gemma":0.00002755393,"domain_scores_codex":[0.9956636,0.0001024995,0.0008485449,0.001012337,0.002127622,0.0002454063],"domain_scores_gemma":[0.9971691,0.0008611649,0.000235252,0.001186534,0.0002943176,0.0002536574],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00000686984,0.000007183105,5.225208e-7,0.00000408019,0.000009015362,0.000006205859,0.00009543802,0.001037613,3.515957e-7,0.3251732,0.6631601,0.01049941],"study_design_scores_gemma":[0.00004427953,0.00001776495,3.799157e-7,0.000007035218,0.000006967734,0.00000147032,0.000006835503,0.02671377,0.000002209733,0.5549295,0.4181367,0.0001330895],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000001492236,0.0004050711,0.1036814,0.002658931,0.0003437897,0.0002299694,0.00005200228,0.0001276902,0.8924997],"genre_scores_gemma":[0.0003651738,0.00007490862,0.002499681,0.002192564,0.000305025,0.000006461412,0.00001685562,0.00002389338,0.9945154],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2450234,"threshold_uncertainty_score":0.9972554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4267274205745191,"score_gpt":0.3984152283939232,"score_spread":0.02831219218059594,"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."}}