{"id":"W7067473289","doi":"","title":"THE LEXICON OF SCIENCE: EXTRACTING THE SCIENTIFIC VOCABULARY FROM WRITTEN AND SPOKEN CORPORA","year":2011,"lang":"en","type":"article","venue":"Scholarship@Western (Western University)","topic":"Prenatal Screening and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Lexicon; Vocabulary; Context (archaeology); Lexical item; Scientific writing; Scientific literature","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003325639,0.0008691251,0.0008991255,0.01625127,0.001356005,0.005170492,0.0009187266,0.001384919,0.004223351],"category_scores_gemma":[0.02473959,0.0007866916,0.0006996801,0.008594643,0.001229894,0.0059774,0.003351543,0.001652259,0.004058395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001326479,"about_ca_system_score_gemma":0.003868276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007182153,"about_ca_topic_score_gemma":0.009014872,"domain_scores_codex":[0.9966988,0.0008385887,0.0007966121,0.0007397562,0.0007232452,0.0002028901],"domain_scores_gemma":[0.9832091,0.0114449,0.001297238,0.001039065,0.002595047,0.0004146469],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004729295,0.0004641689,0.07094998,0.00404468,0.000190291,0.002517461,0.03082613,0.00231222,0.07427638,0.01467481,0.05058721,0.7486837],"study_design_scores_gemma":[0.0003148405,0.000465403,0.3465222,0.002476445,0.0004774741,0.005959637,0.08087718,0.07011422,0.0362054,0.03200191,0.4238872,0.000698309],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6333914,0.005373857,0.1974355,0.002545577,0.0007917021,0.002738809,0.09723987,0.006399579,0.05408367],"genre_scores_gemma":[0.5861523,0.002416453,0.2688932,0.0003791471,0.0003001713,0.002755274,0.132083,0.001184522,0.005836003],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01625127,"threshold_uncertainty_score":0.0175879,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1371057352368748,"score_gpt":0.3145869173135623,"score_spread":0.1774811820766874,"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."}}