{"id":"W2184603562","doi":"","title":"Leveraging Crowdsourced Technical Documentation: Building a Command Thesaurus","year":2013,"lang":"en","type":"article","venue":"","topic":"Hermeneutics and Narrative Identity","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Documentation; Bridging (networking); Thesaurus; Terminology; Controlled vocabulary; World Wide Web; Information retrieval; Technical documentation; Software; Crowdsourcing; Publication; Natural language processing","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009167111,0.001110099,0.0008258719,0.01471855,0.002412952,0.004533396,0.002635093,0.002124256,0.004517057],"category_scores_gemma":[0.04225802,0.0009637842,0.001301308,0.007157294,0.002885274,0.007310006,0.008044401,0.001679612,0.002847896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001481806,"about_ca_system_score_gemma":0.003331844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004446809,"about_ca_topic_score_gemma":0.006659213,"domain_scores_codex":[0.9910656,0.004699802,0.0009357518,0.001229714,0.001884548,0.0001846472],"domain_scores_gemma":[0.9765818,0.01177347,0.001444672,0.005941518,0.003580429,0.0006781878],"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":[0.0003406738,0.0006274704,0.008260204,0.003337163,0.0003001376,0.002597578,0.0441877,0.01968207,0.02785002,0.0787019,0.0331978,0.7809172],"study_design_scores_gemma":[0.0002493634,0.0005321691,0.007721188,0.002631052,0.0003834438,0.003481303,0.02179713,0.254042,0.05246454,0.160893,0.4950818,0.000723009],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05750979,0.001015084,0.9061293,0.001326494,0.0003042455,0.001687629,0.002474988,0.005975963,0.02357648],"genre_scores_gemma":[0.1532353,0.000430761,0.8351386,0.0002360743,0.00007211767,0.0008047522,0.004727949,0.001044246,0.004310254],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01471855,"threshold_uncertainty_score":0.04848087,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03020165808702932,"score_gpt":0.2552580823848339,"score_spread":0.2250564242978046,"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."}}