{"id":"W2515860461","doi":"10.18653/v1/s16-2003","title":"Metaphor as a Medium for Emotion: An Empirical Study","year":2016,"lang":"en","type":"article","venue":"","topic":"Language, Metaphor, and Cognition","field":"Psychology","cited_by":169,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"Leverhulme Trust","keywords":"Metaphor; Literal (mathematical logic); Emotionality; Statement (logic); Meaning (existential); Domain (mathematical analysis); Literal and figurative language; Empirical research; Psychology; Composition (language); Computer science; Cognitive psychology; Linguistics; Natural language processing; Social psychology; Mathematics; Philosophy; Statistics; Algorithm","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":["insufficient_payload"],"category_scores_codex":[0.0004520593,0.0001311038,0.0001917878,0.00008466593,0.00007457101,0.00002217913,0.0001550918,0.00009570899,0.01435348],"category_scores_gemma":[0.00009065428,0.00007231197,0.0001007397,0.0001144624,0.00003780517,0.0001291369,0.00002003034,0.00005041723,0.001496215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000169242,"about_ca_system_score_gemma":0.00002566841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008121083,"about_ca_topic_score_gemma":0.0001441285,"domain_scores_codex":[0.9987394,0.0002030068,0.0002205836,0.0003966897,0.0001782889,0.0002619922],"domain_scores_gemma":[0.999162,0.0001671369,0.00004730704,0.0003836555,0.0001090866,0.0001307744],"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":[0.003444779,0.01840948,0.06950937,0.00004010453,0.002422986,0.0003050131,0.0771727,9.218e-8,0.00997998,0.04012452,0.2405887,0.5380023],"study_design_scores_gemma":[0.032242,0.02042782,0.5164375,0.00004172208,0.00160826,0.0002863672,0.1628039,0.00001936171,0.01013542,0.0675078,0.1865279,0.001961915],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9331132,0.00006018789,0.01310907,0.001885315,0.001161166,0.0008591,0.00001759202,0.0001943288,0.04960007],"genre_scores_gemma":[0.9655955,0.000001657013,0.0003873114,0.001365198,0.0005659612,0.000286219,0.00001204331,0.00002279269,0.03176334],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5360404,"threshold_uncertainty_score":0.9992812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05596706768826435,"score_gpt":0.3884607846801564,"score_spread":0.3324937169918921,"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."}}