{"id":"W2481599432","doi":"10.1017/cbo9780511663659.018","title":"Templates and Affix Ordering","year":2000,"lang":"en","type":"other","venue":"","topic":"Syntax, Semantics, Linguistic Variation","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Affix; Template; Computer science; Natural language processing; Programming language","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00002566202,0.0001364291,0.0001571066,0.0001064907,0.00006519726,0.0001393006,0.00005256785,0.0000749555,0.06938376],"category_scores_gemma":[0.00001877152,0.0001165116,0.00002004846,0.000006308312,0.00005983266,0.00001602695,0.00001703603,0.00005860615,0.0003657666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004449367,"about_ca_system_score_gemma":0.000008783045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0045021,"about_ca_topic_score_gemma":0.01153778,"domain_scores_codex":[0.9995444,0.000007520714,0.0001069039,0.0001589614,0.00007357268,0.0001086373],"domain_scores_gemma":[0.9997647,0.00002741913,0.00005727105,0.000116725,0.00001016601,0.00002373215],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002721492,0.00001968118,0.00003760528,0.0001142712,0.00009281083,0.000006147385,0.008123639,3.205035e-7,0.000001446068,0.7106302,0.2775972,0.003373982],"study_design_scores_gemma":[0.00009270674,0.00001031006,0.000007245705,0.000098899,0.00002924043,0.000001539541,0.0005216339,0.00003814352,0.000002794389,0.01015262,0.9888682,0.0001766745],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00005403712,0.0001965719,0.00003932467,0.0008322521,0.0007409371,0.0001013609,0.00002486995,0.0002695275,0.9977411],"genre_scores_gemma":[0.01011712,0.00009458839,0.0005708568,0.00008425515,0.002633035,0.000003879979,0.00002917285,0.0002004133,0.9862667],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.711271,"threshold_uncertainty_score":0.9314669,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02154403940842076,"score_gpt":0.2234591640648463,"score_spread":0.2019151246564255,"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."}}