{"id":"W4235889089","doi":"10.22215/etd/2014-10965","title":"Semantics and Processing of Weak and Strong Definites in Colloquial Persian: Evidence from an Offline Questionnaire","year":2014,"lang":"en","type":"dissertation","venue":"","topic":"Syntax, Semantics, Linguistic Variation","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Antecedent (behavioral psychology); Presupposition; Linguistics; Suffix; Psychology; Semantics (computer science); Naturalness; Natural language processing; Artificial intelligence; Computer science; Social psychology; Philosophy; Physics","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":[0.001723972,0.0003803868,0.0002437408,0.0006978808,0.0004724318,0.001174006,0.0003833599,0.0005418641,0.004134021],"category_scores_gemma":[0.01174368,0.0002809648,0.00009881011,0.0005093041,0.001298271,0.00147624,0.0006724455,0.0007374331,0.0007155304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004593411,"about_ca_system_score_gemma":0.0003197924,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003192422,"about_ca_topic_score_gemma":0.003262315,"domain_scores_codex":[0.9990215,0.0004903068,0.00007284169,0.0001871997,0.000146475,0.00008156326],"domain_scores_gemma":[0.9907713,0.00610264,0.001045577,0.0006016341,0.001090298,0.0003884792],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.001202643,0.0007760914,0.2214719,0.0005292094,0.00005320263,0.002214409,0.6055743,0.0004262675,0.09405663,0.004062354,0.0009930393,0.06863989],"study_design_scores_gemma":[0.000114824,0.001308012,0.7165422,0.00008539503,0.00004732821,0.00300472,0.2354384,0.002610927,0.01789507,0.00485355,0.01794873,0.0001508016],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980524,0.00003681794,0.0004557232,0.0000327807,0.000002110973,0.00001467963,0.00004708444,0.00001088793,0.001347518],"genre_scores_gemma":[0.9986591,0.00003070791,0.000403356,0.00003149086,0.000002443178,0.00001193015,0.00006807509,0.000008671995,0.0007841139],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004134021,"threshold_uncertainty_score":0.01382971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02984107994064832,"score_gpt":0.279499494589791,"score_spread":0.2496584146491427,"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."}}