{"id":"W4252640808","doi":"10.32920/ryerson.14662626","title":"Mental Time Travel in Depression: Disentangling Cue Valence, Temporal Orientation and Task Instructions","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Identity, Memory, and Therapy","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; Systems, Applications & Products in Data Processing (Canada); University of Waterloo","funders":"","keywords":"Psychology; Valence (chemistry); Fluency; Psychological intervention; Beck Depression Inventory; Chronesthesia; Depression (economics); Verbal fluency test; Clinical psychology; Cognitive psychology; Developmental psychology; Cognition; Episodic memory; Psychiatry; Neuropsychology; Anxiety","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":[],"category_scores_codex":[0.0001704081,0.0002330227,0.0003042345,0.0002411007,0.000122187,0.0001185162,0.0001520557,0.0002871508,0.002643421],"category_scores_gemma":[0.000008649293,0.0002382017,0.00009506995,0.0001650457,0.00008365394,0.0001406552,0.0001797288,0.0004455178,0.00005135168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008002352,"about_ca_system_score_gemma":0.00006097524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001158303,"about_ca_topic_score_gemma":0.0005797526,"domain_scores_codex":[0.9983509,0.0001607401,0.0003855306,0.0006739108,0.0002006244,0.0002283037],"domain_scores_gemma":[0.9993383,0.00002721612,0.0001356398,0.0003719513,0.00004312804,0.0000837162],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000209132,0.0009291248,0.9344623,0.0001793077,0.0003437241,0.0002634641,0.03012297,0.00004045139,0.002058495,0.001525207,0.003048807,0.02681698],"study_design_scores_gemma":[0.005527629,0.00009838986,0.9508571,0.0005611232,0.0001653151,0.0003327153,0.03085336,0.001142657,0.001449624,0.00620985,0.001476625,0.001325618],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9781442,0.0008742444,0.0005179237,0.0001006923,0.005037662,0.000450046,0.00006289787,0.00005610572,0.01475617],"genre_scores_gemma":[0.990821,0.0002454211,0.001016698,0.00009735472,0.0003355551,0.00009018093,0.00058982,0.00003202533,0.00677197],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02549137,"threshold_uncertainty_score":0.9982683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01719071850979567,"score_gpt":0.3140426422189533,"score_spread":0.2968519237091577,"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."}}