{"id":"W2099801661","doi":"10.1080/00085006.2003.11092338","title":"From PIE to OCS: ALG or MAC?","year":2003,"lang":"en","type":"article","venue":"Canadian Slavonic Papers","topic":"Linguistics, Language Diversity, and Identity","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Business","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":[0.0001758841,0.0005168794,0.0003363186,0.0008251735,0.0005608171,0.002168161,0.0007026611,0.0007699251,0.2339865],"category_scores_gemma":[0.0004716543,0.0001328118,0.0003219877,0.001497733,0.0004711522,0.002304573,0.001764989,0.0007246103,0.0937458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000629917,"about_ca_system_score_gemma":0.000616801,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003003352,"about_ca_topic_score_gemma":0.003637336,"domain_scores_codex":[0.999877,0.00002031038,0.000009112549,0.00003147278,0.00003152235,0.00003068262],"domain_scores_gemma":[0.9998827,0.00001531814,0.00001773259,0.00001035944,0.0000401334,0.00003363995],"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":[0.0002153342,0.00004042654,0.0005464478,0.003399635,0.00002352917,0.000556308,0.0005102039,0.0001574971,0.002073194,0.03248242,0.457059,0.5029361],"study_design_scores_gemma":[0.000003173338,0.00001061847,0.0006596061,0.0002275467,0.000002252054,0.0001501944,0.0000942136,0.00001152095,0.0001287053,0.0006281382,0.9980812,0.000002857567],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.009800137,0.1501352,0.001912692,0.01410766,0.0403569,0.0001563779,0.00353791,0.001037708,0.7789555],"genre_scores_gemma":[0.09074531,0.09742079,0.002561708,0.009293674,0.008084227,0.0001971214,0.003951891,0.0008869045,0.7868583],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2339865,"threshold_uncertainty_score":0.7827629,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02658324850777475,"score_gpt":0.2121220767198712,"score_spread":0.1855388282120965,"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."}}