{"id":"W2372095876","doi":"","title":"A Comparative Study of Chinese Ha(哈) and English Eh","year":2008,"lang":"en","type":"article","venue":"Waiguoyu","topic":"Linguistic Variation and Morphology","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Interrogative; Linguistics; Cohesion (chemistry); Sentence; Psychology; Politeness; Interrogative word; Modality (human–computer interaction); Computer science; Function (biology); Natural language processing; Artificial intelligence; Philosophy; Physics; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.000497182,0.0001936063,0.0001945831,0.001383343,0.001894999,0.0008436438,0.0003264495,0.0002103619,0.003547355],"category_scores_gemma":[0.001776989,0.0001157671,0.0001712117,0.002496458,0.001342485,0.000562727,0.0008507692,0.0002946954,0.0001527729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002885523,"about_ca_system_score_gemma":0.002607957,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4205248,"about_ca_topic_score_gemma":0.5522078,"domain_scores_codex":[0.9996601,0.00004219961,0.00002369356,0.00004944751,0.000104163,0.0001203141],"domain_scores_gemma":[0.9992176,0.0002568765,0.0000744061,0.00004861055,0.0002911986,0.0001112278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.00152299,0.000153383,0.2553991,0.0008951367,0.0001305567,0.006679509,0.4417875,0.0003421541,0.07334983,0.03488518,0.002692119,0.1821626],"study_design_scores_gemma":[0.00002293718,0.0002564597,0.8190647,0.00005030753,0.00008625886,0.001769417,0.1320425,0.0003820041,0.005181117,0.0008579267,0.04020987,0.00007651169],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9877265,0.0002383752,0.0001617308,0.00004918376,0.000009050615,0.00001331218,0.00007954396,0.00000416278,0.01171806],"genre_scores_gemma":[0.9975792,0.0001268065,0.0002253151,0.00001799325,0.000003732068,0.000006017438,0.000074482,0.000004339223,0.001962245],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4205248,"threshold_uncertainty_score":0.8361541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04920279635144693,"score_gpt":0.3532423285619758,"score_spread":0.3040395322105289,"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."}}