{"id":"W2770816112","doi":"10.1016/j.actpsy.2017.11.003","title":"Mapping language to visual referents: Does the degree of image realism matter?","year":2017,"lang":"en","type":"article","venue":"Acta Psychologica","topic":"Language, Metaphor, and Cognition","field":"Psychology","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Referent; Noun; Verb; Comprehension; Visual language; Psychology; Situated; Cognition; Computer science; Set (abstract data type); Stimulus (psychology); Cognitive psychology; Artificial intelligence; Natural language processing; Communication; Linguistics","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":[0.004783805,0.0004190335,0.0005225694,0.001132195,0.0007601137,0.005898549,0.001014621,0.002119222,0.01492185],"category_scores_gemma":[0.06946594,0.0005606737,0.0005713865,0.0005492773,0.005817251,0.01027801,0.002334437,0.002369951,0.001307575],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005262646,"about_ca_system_score_gemma":0.0006241053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009803066,"about_ca_topic_score_gemma":0.000738475,"domain_scores_codex":[0.9968495,0.001515717,0.0001508316,0.0006839565,0.0005002318,0.0002997931],"domain_scores_gemma":[0.9722914,0.01780145,0.003296371,0.003564821,0.001707646,0.001338303],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.005431159,0.001263551,0.189223,0.001611121,0.0009364426,0.001152341,0.04246277,0.006944797,0.1012947,0.4070137,0.004482724,0.2381837],"study_design_scores_gemma":[0.0006367064,0.0009564577,0.271031,0.0006466695,0.000557287,0.002585756,0.02412753,0.01628891,0.0142212,0.6567232,0.01187832,0.0003469141],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8657374,0.001313325,0.03372025,0.005715406,0.0002766995,0.00008226244,0.0001980628,0.0001807801,0.0927759],"genre_scores_gemma":[0.9969954,0.0002045323,0.001665002,0.0001315632,0.00004265936,0.00001296601,0.0000492654,0.00007757213,0.0008209185],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01492185,"threshold_uncertainty_score":0.04991853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06616392010271059,"score_gpt":0.3728946468136727,"score_spread":0.3067307267109621,"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."}}