{"id":"W2397694745","doi":"10.63317/5agbhnncc4sh","title":"Experiments in Topic Detection","year":2002,"lang":"en","type":"article","venue":"","topic":"Text and Document Classification Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Lethbridge","funders":"","keywords":"WordNet; Computer science; Thesaurus; Information retrieval; Natural language processing; Precision and recall; Implementation; Artificial intelligence; Recall; Domain (mathematical analysis); Linguistics; Mathematics","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":[0.007538599,0.001411879,0.001798843,0.002197769,0.00224716,0.002223591,0.001851582,0.002936569,0.006164605],"category_scores_gemma":[0.02513115,0.0005907062,0.001179909,0.003703901,0.0008565215,0.002937018,0.00152058,0.00156046,0.003215452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000944515,"about_ca_system_score_gemma":0.0008361509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004377243,"about_ca_topic_score_gemma":0.0028512,"domain_scores_codex":[0.991874,0.00371896,0.0009891171,0.001806902,0.001096323,0.0005147324],"domain_scores_gemma":[0.9718224,0.02195936,0.0004955865,0.00238367,0.002586468,0.0007524819],"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":[0.01090088,0.01403555,0.02613133,0.005045076,0.0008812044,0.003260318,0.006707224,0.05108731,0.0811077,0.007079313,0.06605441,0.7277097],"study_design_scores_gemma":[0.005930576,0.01261226,0.04952969,0.0005440509,0.001289282,0.007084026,0.006648994,0.561979,0.1756325,0.02350984,0.1546112,0.0006284812],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7959289,0.007562851,0.1399143,0.00209193,0.001171191,0.004876769,0.009299017,0.01329979,0.02585528],"genre_scores_gemma":[0.6062749,0.001801802,0.3505795,0.0009996048,0.0005252911,0.002909912,0.01854304,0.001107513,0.01725848],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007538599,"threshold_uncertainty_score":0.03986841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04286456784919886,"score_gpt":0.2522528984422731,"score_spread":0.2093883305930742,"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."}}