{"id":"W3132186272","doi":"10.1007/978-3-642-25324-9","title":"Advances in Artificial Intelligence","year":2011,"lang":"en","type":"book","venue":"Lecture notes in computer science","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":80,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Artificial intelligence; Management science; Economics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007888244,0.0002881413,0.0004553366,0.0009026083,0.00009819688,0.00005644301,0.0005204779,0.0003361629,0.000119006],"category_scores_gemma":[0.0003869962,0.0002609672,0.00007300696,0.001018451,0.0007138236,0.0002893836,0.000128574,0.0009541307,0.0001459923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006550193,"about_ca_system_score_gemma":0.002306487,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001951778,"about_ca_topic_score_gemma":0.001322779,"domain_scores_codex":[0.997277,0.00003537419,0.0007456472,0.0008602085,0.0005041097,0.0005776406],"domain_scores_gemma":[0.9984779,0.0003856553,0.0001720288,0.0005631461,0.0002361982,0.0001651015],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003793343,0.00007987666,0.0006747069,0.0001092056,0.000001168191,0.00004381934,0.002058838,0.001733769,0.0000217458,0.0009647983,0.00001261962,0.9942615],"study_design_scores_gemma":[0.00002435965,0.0006652302,0.0003797745,0.002225597,0.00001719572,0.00009015261,0.0000124933,0.05041811,0.02090807,0.9209337,0.003683958,0.0006413253],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001192856,0.002438424,0.9838045,0.0008734078,0.003126813,0.0006604029,0.000001798136,0.00005585023,0.007845934],"genre_scores_gemma":[0.9149313,0.001978072,0.07575243,0.002942157,0.003445867,0.00006122156,0.00003277883,0.00006790104,0.0007882686],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9936202,"threshold_uncertainty_score":0.9999843,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1201966220307467,"score_gpt":0.3958362517093508,"score_spread":0.2756396296786042,"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."}}