{"id":"W2177656103","doi":"","title":"Identification of Truth and Deception in Text: Application of Vector Space Model to Rhetorical Structure Theory","year":2012,"lang":"en","type":"article","venue":"","topic":"Deception detection and forensic psychology","field":"Psychology","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Deception; Rhetorical question; Identification (biology); Complement (music); Coherence (philosophical gambling strategy); Computer science; Pragmatics; Artificial intelligence; Space (punctuation); Natural language processing; Linguistics; Epistemology; Self-deception; Psychology; Social psychology; Mathematics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035335,0.00008022102,0.0001519092,0.0002189072,0.00001429945,0.000002982379,0.00006652706,0.0001431506,0.0004852847],"category_scores_gemma":[0.00004865973,0.00007383002,0.00002734876,0.0002775258,0.00006915588,0.00007563359,0.00001624711,0.00008255841,0.00005221733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002732585,"about_ca_system_score_gemma":0.000004815643,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001737529,"about_ca_topic_score_gemma":0.00001786231,"domain_scores_codex":[0.9991303,0.00009601237,0.0003411348,0.0001954105,0.00009681594,0.0001403361],"domain_scores_gemma":[0.9994048,0.00006218744,0.0001434146,0.0002646852,0.00005338951,0.00007144602],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0004467334,0.0002944772,0.01324769,0.00001963279,0.00002457956,6.117279e-8,0.005067775,0.0001846777,0.2507767,0.659262,0.001020389,0.06965521],"study_design_scores_gemma":[0.001324942,0.0001679149,0.9481163,0.000008600488,0.00003152209,0.00002300356,0.001830337,0.003653311,0.01809853,0.02545398,0.001036944,0.0002546307],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.766725,0.00004903014,0.2293988,0.0001172003,0.0004628944,0.0002088533,0.00001075837,0.00002083656,0.003006576],"genre_scores_gemma":[0.9983957,0.000003653105,0.000660922,0.00006766091,0.00005169266,0.00002689555,0.00000566175,0.000009626115,0.0007782168],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9348686,"threshold_uncertainty_score":0.5313527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02106446987942143,"score_gpt":0.3357101699172008,"score_spread":0.3146457000377794,"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."}}