{"id":"W93917463","doi":"","title":"Authorship Attribution for Small Texts: Literary and Forensic Experiments.","year":2007,"lang":"en","type":"article","venue":"PAN","topic":"Authorship Attribution and Profiling","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Attribution; Authorship attribution; Psychology; History; Computer science; Linguistics; Social psychology; Natural language processing; Philosophy","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":[0.0103413,0.0005769152,0.0005483904,0.002335891,0.002186236,0.00212587,0.001122117,0.001690658,0.004647957],"category_scores_gemma":[0.1031242,0.0003101622,0.000289264,0.002388262,0.001782792,0.003232916,0.002356799,0.001537149,0.001260132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005317935,"about_ca_system_score_gemma":0.000496336,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003025742,"about_ca_topic_score_gemma":0.0003470231,"domain_scores_codex":[0.9912937,0.005172874,0.0005245213,0.001132817,0.001587919,0.0002881668],"domain_scores_gemma":[0.8066755,0.1530006,0.01006963,0.02185409,0.006282801,0.00211736],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.02223603,0.02439225,0.07759953,0.002680194,0.0006260879,0.002981199,0.02838924,0.02628573,0.1297161,0.05639623,0.03560634,0.5930911],"study_design_scores_gemma":[0.001978973,0.008831976,0.09181485,0.0006410611,0.0004977196,0.00696717,0.01517916,0.4837612,0.2376699,0.117805,0.03443926,0.0004137384],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9789444,0.0003354757,0.01306144,0.0004634887,0.0002165756,0.0002996818,0.0007889948,0.0003122915,0.005577595],"genre_scores_gemma":[0.9829966,0.0001363967,0.01269673,0.00008626075,0.0001190277,0.0001738866,0.0008666987,0.00007314964,0.002851297],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0103413,"threshold_uncertainty_score":0.05469066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06904991508512409,"score_gpt":0.319997208466426,"score_spread":0.2509472933813019,"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."}}