{"id":"W4390481401","doi":"10.1109/ssci52147.2023.10372049","title":"Causal Models Applied to the Patterns of Human Migration due to Climate Change","year":2023,"lang":"en","type":"article","venue":"","topic":"Climate Change, Adaptation, Migration","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Context (archaeology); Climate change; Corporate governance; Bayesian network; Affect (linguistics); Computer science; Risk analysis (engineering); Business; Political science; Artificial intelligence; Geography; Sociology; Ecology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007764097,0.00008774045,0.0001210338,0.0001520564,0.0004384393,0.00006448434,0.0001973457,0.00005561699,0.0001386889],"category_scores_gemma":[0.00003261732,0.00007067731,0.00003423599,0.0006654867,0.0000242739,0.0001851264,0.00006426856,0.00003888477,0.0002542954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007687314,"about_ca_system_score_gemma":0.00002029692,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01658969,"about_ca_topic_score_gemma":0.5034109,"domain_scores_codex":[0.9988102,0.00007008888,0.0002163155,0.0001994334,0.0004097327,0.0002941915],"domain_scores_gemma":[0.9994706,0.00007187788,0.00006877304,0.000186624,0.0001130517,0.00008905958],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00002384989,0.00005758508,0.003469202,0.00004413998,0.00001338388,0.000001948337,0.6145045,0.001601747,0.009956723,0.3535196,0.007803408,0.009003958],"study_design_scores_gemma":[0.001170735,0.0005984675,0.3264898,0.0002520152,0.0001272031,0.000001345387,0.5843728,0.02265386,0.01151591,0.02139491,0.02980394,0.001619024],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.972785,0.000004132419,0.002848882,0.01343631,0.0001914821,0.001238606,0.00006976276,0.0002045719,0.009221238],"genre_scores_gemma":[0.9975455,0.00005592608,0.0001012777,0.0008261173,0.0003457067,0.0003299451,0.00008802204,0.00001405286,0.0006934485],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4868213,"threshold_uncertainty_score":0.9899589,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2397731761684925,"score_gpt":0.3630510303718016,"score_spread":0.1232778542033091,"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."}}