{"id":"W6887721427","doi":"10.17605/osf.io/kxjwm","title":"Assessing alexithymia for positive and negative emotions: the role of granularity and dialecticism","year":2023,"lang":"en","type":"article","venue":"OSF Preprints (OSF Preprints)","topic":"Psychosomatic Disorders and Their Treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Alexithymia; Toronto Alexithymia Scale; Scale (ratio); Granularity; Personality","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003129765,0.000224523,0.0003121292,0.001126962,0.0005087136,0.001757422,0.0002872391,0.0003467116,0.001956783],"category_scores_gemma":[0.01220164,0.0001581718,0.0002986003,0.0006055358,0.0007032744,0.001504145,0.002022574,0.0007168708,0.0002288822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000537471,"about_ca_system_score_gemma":0.0003936349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003476998,"about_ca_topic_score_gemma":0.0006952762,"domain_scores_codex":[0.9968093,0.001409186,0.0004369728,0.0003918179,0.0007935868,0.0001592436],"domain_scores_gemma":[0.9938897,0.003501004,0.001097398,0.0007531394,0.0004924985,0.0002662133],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001806966,0.0006081481,0.4799809,0.000985901,0.0003863304,0.0005977055,0.03721943,0.0008710385,0.07188348,0.0180331,0.0007873636,0.3868397],"study_design_scores_gemma":[0.0001624388,0.0005956015,0.9283499,0.000377172,0.0001725157,0.002924848,0.01407867,0.004193949,0.01292764,0.02862242,0.007481682,0.0001132347],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9590403,0.0006878601,0.02019059,0.0002663421,0.00003590266,0.0003106511,0.0001057608,0.00007124223,0.01929127],"genre_scores_gemma":[0.9908383,0.0001383453,0.008195784,0.00004804796,0.000009583738,0.0001759059,0.00006111309,0.00001391595,0.0005190527],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003129765,"threshold_uncertainty_score":0.01655197,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01947949102767406,"score_gpt":0.3016301623971116,"score_spread":0.2821506713694376,"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."}}