{"id":"W4243393140","doi":"10.1007/978-3-030-57321-8","title":"Machine Learning and Knowledge Extraction","year":2020,"lang":"en","type":"book","venue":"Lecture notes in computer science","topic":"Computational Physics and Python Applications","field":"Computer Science","cited_by":51,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Information extraction; Artificial intelligence; Knowledge extraction; Extraction (chemistry); Machine learning; Knowledge graph","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":[0.0003322293,0.000272842,0.000269294,0.0003118795,0.0001882837,0.0003297823,0.001075867,0.0001146563,0.000009201375],"category_scores_gemma":[0.00005027588,0.0002724869,0.0000571757,0.0007157916,0.0002350649,0.0003755161,0.00100048,0.0007926125,0.0000542879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002964462,"about_ca_system_score_gemma":0.001078057,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001276,"about_ca_topic_score_gemma":0.00001790302,"domain_scores_codex":[0.9979842,0.00004673351,0.0002656558,0.001028666,0.000394537,0.0002802358],"domain_scores_gemma":[0.9985741,0.0005909806,0.0001709967,0.0003658924,0.0001442252,0.0001537657],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001738098,0.00003258719,0.0000401655,0.00003749756,0.000006282334,0.00001092839,0.0009297509,0.01236681,0.0001487919,0.04566709,0.0002254818,0.9405329],"study_design_scores_gemma":[0.000095656,0.00005255618,0.000108615,0.00004908812,0.000003146997,0.00002502332,4.294946e-8,0.7933227,0.00006644028,0.1470204,0.0590071,0.0002492265],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000008625876,0.001520812,0.9900922,0.001126284,0.0005667072,0.0002020765,0.000002113819,0.0001533445,0.006327795],"genre_scores_gemma":[0.1940033,0.0003627023,0.7981426,0.002239686,0.001884418,0.00004625615,0.00006790701,0.00007263714,0.003180514],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9402837,"threshold_uncertainty_score":0.9999728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01511105813164199,"score_gpt":0.2806734722842492,"score_spread":0.2655624141526072,"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."}}