{"id":"W2911214330","doi":"10.5539/ijel.v9n1p421","title":"Impact of Number and Type of Figures’ Identification on Accessing Caricatures’ Meaning","year":2019,"lang":"en","type":"article","venue":"International Journal of English Linguistics","topic":"Language, Metaphor, and Cognition","field":"Psychology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Identification (biology); Meaning (existential); Reading (process); Point (geometry); Type (biology); Sequence (biology); Term (time); Computer science; Epistemology; Mathematics; Linguistics; Philosophy; Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.000299208,0.00008007856,0.0001805922,0.0001589801,0.0000123833,0.00003280918,0.000208635,0.00007678514,0.0004295955],"category_scores_gemma":[0.009989395,0.00006628997,0.000101645,0.0000893534,0.000032424,0.00004754771,0.00002132732,0.0002017298,0.00000935525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004318694,"about_ca_system_score_gemma":0.00005210601,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003782447,"about_ca_topic_score_gemma":0.000001247668,"domain_scores_codex":[0.9989604,0.00005536524,0.0004649243,0.00009592083,0.0003456202,0.00007780238],"domain_scores_gemma":[0.9900848,0.0002094696,0.0007416546,0.0001122245,0.008814151,0.00003769025],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004742604,0.001912026,0.747027,0.0001904849,0.004769167,0.0001456761,0.03734669,0.001117549,0.01297252,0.1501473,0.02043716,0.01919176],"study_design_scores_gemma":[0.005894161,0.001625025,0.9369288,0.001132289,0.0006242943,0.00006141774,0.004671052,0.0002430863,0.01312446,0.01886793,0.01622147,0.0006059895],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8940829,0.0002063449,0.00008558122,0.000003210445,0.009278006,0.00004482722,0.00002837958,0.000004986426,0.09626575],"genre_scores_gemma":[0.9973009,0.00003087515,0.0002144037,0.00002488656,0.002203316,3.10615e-7,0.00001530381,0.00001151911,0.0001984659],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1899018,"threshold_uncertainty_score":0.9983499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02506532001650903,"score_gpt":0.3742456866540466,"score_spread":0.3491803666375376,"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."}}