{"id":"W1964688066","doi":"10.3765/sp.3.9","title":"Cross-linguistic variation in modality systems: The role of mood","year":2010,"lang":"en","type":"article","venue":"Semantics and Pragmatics","topic":"Syntax, Semantics, Linguistic Variation","field":"Arts and Humanities","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Modal verb; Linguistics; Implicature; Politeness; Context (archaeology); Psychology; Modality (human–computer interaction); Modal; Variation (astronomy); Pragmatics; Computer science; Artificial intelligence; Philosophy; History; Verb","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001428784,0.0001926657,0.0002494755,0.001150543,0.000852174,0.003199599,0.0004127591,0.000478904,0.004636619],"category_scores_gemma":[0.004275439,0.000289684,0.0002834261,0.0008965215,0.002416726,0.002337259,0.002705192,0.0009400428,0.0004042207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009142748,"about_ca_system_score_gemma":0.0002131831,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001530089,"about_ca_topic_score_gemma":0.001929031,"domain_scores_codex":[0.9989208,0.0005452455,0.00005513807,0.0002130659,0.000162057,0.0001037613],"domain_scores_gemma":[0.9976507,0.001354024,0.0002558236,0.0003208992,0.0002911901,0.0001274532],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0008930922,0.0001691885,0.09694459,0.0004207142,0.0003204588,0.001486972,0.1030906,0.001485259,0.1566893,0.4525172,0.002687151,0.1832956],"study_design_scores_gemma":[0.0001843938,0.0005324616,0.5863072,0.0002767972,0.0003410885,0.003273978,0.02884218,0.009119888,0.01670841,0.3082651,0.04583312,0.0003152676],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.832379,0.0007770505,0.0185149,0.0005554259,0.00004970569,0.00002769352,0.0001866686,0.0001519604,0.1473576],"genre_scores_gemma":[0.997577,0.00006834369,0.00131124,0.00006283573,0.00001435183,0.00001111347,0.00004046539,0.00004622589,0.0008684593],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004636619,"threshold_uncertainty_score":0.01551104,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01345314954393982,"score_gpt":0.2476936881836236,"score_spread":0.2342405386396838,"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."}}