{"id":"W1974289591","doi":"10.5539/ass.v5n3p25","title":"A Cognitive Model for Recognition of Genre","year":2009,"lang":"en","type":"article","venue":"Asian Social Science","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Schema (genetic algorithms); Computer science; Cognition; Cognitive model; Image schema; Thread (computing); Top-down and bottom-up design; Natural language processing; Cognitive science; Artificial intelligence; Linguistics; Psychology; Cognitive linguistics; Information retrieval","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.002900032,0.0005838631,0.000333506,0.003185115,0.0009930374,0.00453263,0.001954965,0.001371369,0.005447965],"category_scores_gemma":[0.007731136,0.0003527398,0.001877765,0.001615819,0.00469794,0.009779604,0.002116341,0.001670858,0.0009371043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001841042,"about_ca_system_score_gemma":0.001140538,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003591237,"about_ca_topic_score_gemma":0.001615304,"domain_scores_codex":[0.9981609,0.0005787722,0.0001135021,0.0004204422,0.0005556155,0.000170806],"domain_scores_gemma":[0.9969906,0.001318967,0.0003552579,0.0004955323,0.0006076616,0.0002319463],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006247409,0.00009443134,0.006277277,0.0002158406,0.00006149713,0.0002642842,0.01212291,0.003739706,0.003284505,0.907073,0.00231274,0.06449139],"study_design_scores_gemma":[0.00004244762,0.0001615619,0.009760253,0.0001205054,0.0000655089,0.0007125189,0.004099537,0.04623307,0.001429068,0.9155163,0.02178938,0.00006987206],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1122535,0.0007723827,0.6782061,0.004532616,0.0002144322,0.0003603395,0.0003353486,0.0005193676,0.202806],"genre_scores_gemma":[0.8106465,0.0005005803,0.1770596,0.0008388393,0.0001386045,0.0003346681,0.000487759,0.00006870012,0.009924771],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005447965,"threshold_uncertainty_score":0.01822519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03027785619335693,"score_gpt":0.3275583577971719,"score_spread":0.2972805016038149,"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."}}