{"id":"W2046563305","doi":"10.1524/stuf.2008.0025","title":"Analyzing feature consistency using dissimilarity matrices","year":2008,"lang":"en","type":"article","venue":"Language Typology and Universals","topic":"Language and cultural evolution","field":"Social Sciences","cited_by":65,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Congruence (geometry); Feature (linguistics); Consistency (knowledge bases); Computer science; Coherence (philosophical gambling strategy); Artificial intelligence; Natural language processing; Mathematics; Statistics; Linguistics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001187099,0.00006723058,0.0001173076,0.00004750206,0.0008274887,0.00001204747,0.000078137,0.0001456013,0.0002960126],"category_scores_gemma":[0.00007594546,0.000056257,0.00003579317,0.000176633,0.0004097226,0.0001955872,0.00002564887,0.0001097049,0.000005746578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003572404,"about_ca_system_score_gemma":0.00006111839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004399601,"about_ca_topic_score_gemma":0.002047451,"domain_scores_codex":[0.9994026,0.000141378,0.00005838984,0.0001358077,0.00006972723,0.0001920608],"domain_scores_gemma":[0.9997256,0.00005071927,0.0000481235,0.00007186862,0.00003366891,0.0000700579],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001614361,0.000144607,0.2814254,0.00005961806,0.0002691949,0.002948693,0.449482,0.00001297222,0.01382498,0.2353811,0.008831317,0.007458669],"study_design_scores_gemma":[0.002444193,0.0001908133,0.1418971,0.0001199544,0.0005922245,0.0006810939,0.7902966,0.0002271878,0.001332447,0.002857508,0.0578239,0.001537025],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9650794,0.005485507,0.00006128063,0.000731115,0.00009590069,0.00006675395,0.00000646509,0.0000644918,0.02840913],"genre_scores_gemma":[0.9945129,0.000615303,0.0006595943,0.0001511602,0.0001328084,3.243884e-7,0.000006433658,0.000003208823,0.003918319],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3408145,"threshold_uncertainty_score":0.6650911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02279714753556158,"score_gpt":0.3002996205576565,"score_spread":0.2775024730220949,"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."}}