{"id":"W4416676327","doi":"10.1007/978-981-95-4960-3_23","title":"Causal Temporal Transformer: An Integrated Framework for Temporal Causal Discovery and Multi-target Prediction","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University; Royal Military College of Canada; University of Ottawa","funders":"","keywords":"Interpretability; Causal model; Causality (physics); Causal inference; Causal analysis; Mechanism (biology); Temporal database; Causal structure","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":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0009561021,0.0007513203,0.0007220075,0.0007504722,0.000440491,0.001191374,0.001973786,0.0007459352,0.000005178596],"category_scores_gemma":[0.0001274693,0.000666147,0.000149609,0.0005790627,0.0007210114,0.001789742,0.0003371683,0.001285117,0.000002448918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002394138,"about_ca_system_score_gemma":0.001308299,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001707691,"about_ca_topic_score_gemma":0.0003023515,"domain_scores_codex":[0.995657,0.00006174159,0.0007473923,0.002068623,0.0006677724,0.0007974302],"domain_scores_gemma":[0.9976379,0.0004461044,0.0002464836,0.001051551,0.0003329685,0.0002850041],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001037321,0.0002128943,0.00142928,0.0002808799,0.0000704562,0.00006566658,0.002302928,0.01946578,0.0002061068,0.110975,0.00008376584,0.8648035],"study_design_scores_gemma":[0.0004024133,0.0005123488,0.0001176708,0.0006993786,0.00001891683,0.00002997172,0.000001075744,0.8034127,0.0005308036,0.1930797,0.0005623559,0.0006326755],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001958246,0.0004133975,0.995261,0.0005632227,0.002203488,0.0007820002,0.0001646943,0.0003048042,0.0001115763],"genre_scores_gemma":[0.1913225,0.00004807344,0.8070722,0.0007139024,0.0003248101,0.00003745979,0.00009117109,0.00003471843,0.0003551425],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8641708,"threshold_uncertainty_score":0.9998455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0255903492040286,"score_gpt":0.2782170539429746,"score_spread":0.2526267047389461,"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."}}