{"id":"W4412725067","doi":"10.3390/e27070732","title":"Compositional Causal Identification from Imperfect or Disturbing Observations","year":2025,"lang":"en","type":"article","venue":"Entropy","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Perimeter Institute","funders":"Ministry of Colleges and Universities; Institut Périmètre de physique théorique; Government of Canada; John Templeton Foundation","keywords":"Imperfect; Identification (biology); Computer science; Econometrics; Statistical physics; Artificial intelligence; Mathematics; Biology; Physics; 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":[0.00008576615,0.00006811489,0.00007308731,0.00002718071,0.000197179,0.0001219535,0.0003651208,0.00003578792,0.00008465502],"category_scores_gemma":[0.0001059978,0.00005904384,0.00003375168,0.0002376447,0.00002285143,0.0001707733,0.0001227473,0.00007697384,0.0000358349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003509593,"about_ca_system_score_gemma":0.000053346,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004458178,"about_ca_topic_score_gemma":0.000005474488,"domain_scores_codex":[0.9993458,0.00003388851,0.000155888,0.0002371967,0.0001055538,0.0001216123],"domain_scores_gemma":[0.9994209,0.0001449417,0.00004914198,0.0002902414,0.00006803279,0.00002671614],"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":[0.00001846858,0.0001079598,0.01533167,0.00002075201,0.0000607952,0.00001637444,0.0003452062,0.0006079969,0.4297236,0.5368218,0.01524969,0.001695699],"study_design_scores_gemma":[0.0008626442,0.00003354517,0.5418497,0.0001062212,0.00003516214,0.000009072467,0.00008722353,0.1196596,0.1504541,0.130169,0.05636512,0.0003686171],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1913376,0.00007724488,0.7914475,0.01289647,0.0006867762,0.0001141649,0.00001560654,0.0001804033,0.003244153],"genre_scores_gemma":[0.9874638,0.00000310371,0.008688766,0.0003469481,0.00007302587,0.00001859185,0.00008353241,8.130875e-7,0.003321425],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7961262,"threshold_uncertainty_score":0.2407738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02011076653612051,"score_gpt":0.2531604136176121,"score_spread":0.2330496470814916,"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."}}