{"id":"W4395049151","doi":"10.1075/rcl.00184.luo","title":"Testing the benefits of relating figurative idioms to their literal underpinnings","year":2024,"lang":"en","type":"article","venue":"Review of Cognitive Linguistics","topic":"Language, Metaphor, and Cognition","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Literal and figurative language; Literal (mathematical logic); Linguistics; Psychology; Computer science; Natural language processing; Philosophy","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":[0.002780315,0.000406764,0.0003276755,0.0003814813,0.0002608981,0.001072542,0.0005318454,0.0004908539,0.002845002],"category_scores_gemma":[0.01532358,0.0002194421,0.0002071625,0.0003216937,0.001520288,0.001329172,0.001221387,0.0009747592,0.0003604722],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000266862,"about_ca_system_score_gemma":0.0003425757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003959762,"about_ca_topic_score_gemma":0.0007439903,"domain_scores_codex":[0.9986828,0.0008366461,0.00007423589,0.0001276672,0.0002231528,0.0000554802],"domain_scores_gemma":[0.9885726,0.009046718,0.00116729,0.0005498305,0.0003833985,0.0002802431],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.003438028,0.01016203,0.04957289,0.00442242,0.0001864195,0.001278957,0.07169167,0.001366287,0.3136507,0.006429461,0.001286565,0.5365146],"study_design_scores_gemma":[0.0007086213,0.04862794,0.4526641,0.003283821,0.0009514341,0.003458438,0.06932114,0.006915975,0.3570663,0.02425195,0.03242584,0.0003245772],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953339,0.0002874983,0.001708602,0.00008758928,0.00001200876,0.00005966864,0.00001192806,0.00002085672,0.002477965],"genre_scores_gemma":[0.9927515,0.0005327578,0.005843184,0.00007600198,0.000008576658,0.00008432428,0.00002407412,0.00001235734,0.0006673428],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002845002,"threshold_uncertainty_score":0.01470393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05854309881306338,"score_gpt":0.3550941379455705,"score_spread":0.2965510391325071,"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."}}