{"id":"W4244478245","doi":"10.1115/1.4037817","title":"Automated Extraction of Function Knowledge From Text","year":2017,"lang":"en","type":"article","venue":"Journal of Mechanical Design","topic":"Software Engineering Research","field":"Computer Science","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"Autodesk (Canada)","funders":"Oregon State University","keywords":"WordNet; Computer science; Natural language processing; Word2vec; Knowledge base; Parsing; Function (biology); Artificial intelligence; Information retrieval; Knowledge extraction; Artifact (error); Information extraction","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":[],"consensus_categories":[],"category_scores_codex":[0.001272492,0.00008099715,0.0002050322,0.0001296664,0.00009414653,0.0001306887,0.001046397,0.00009817346,0.00003283822],"category_scores_gemma":[0.002240515,0.00006719747,0.00009626728,0.0001018436,0.00001930975,0.0006852879,0.0001239009,0.0002862307,0.00004046702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000649042,"about_ca_system_score_gemma":0.0001281991,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001318099,"about_ca_topic_score_gemma":6.190268e-7,"domain_scores_codex":[0.9988273,0.0001290239,0.000357946,0.0001300335,0.0004090162,0.0001466969],"domain_scores_gemma":[0.9975765,0.001060547,0.0004251743,0.0004875963,0.0003315111,0.0001186327],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004736441,0.0007558204,0.0005404699,0.00006631931,0.0003450394,0.0002008865,0.0002973055,0.003103993,0.7711106,0.009128362,0.01948239,0.1944952],"study_design_scores_gemma":[0.001557656,0.001514978,0.06981964,0.0003253686,0.00005126923,0.0001349542,0.00001195825,0.7522236,0.1577703,0.0152684,0.001080898,0.0002410222],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01939526,0.0001635179,0.9788017,0.0001671804,0.001280923,0.000059052,5.40079e-7,0.00009172497,0.00004013524],"genre_scores_gemma":[0.909573,0.00001955107,0.09020011,0.000005387655,0.0001486343,0.000001170755,1.167641e-7,0.00000790795,0.00004411094],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8901777,"threshold_uncertainty_score":0.2740233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05922149367044244,"score_gpt":0.329604316374932,"score_spread":0.2703828227044895,"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."}}