{"id":"W4411404412","doi":"10.1071/ep24435","title":"Session 20. Oral Presentation for: Causal networks as a tool to assess environmental risk of CO2 leakage","year":2025,"lang":"en","type":"article","venue":"Australian Energy Producers journal.","topic":"CO2 Sequestration and Geologic Interactions","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kensington Health","funders":"","keywords":"Leakage (economics); Risk assessment; Carbon capture and storage (timeline); Greenhouse gas; Risk analysis (engineering); Stressor; Climate change; Environmental resource management; Environmental science; Environmental planning; Computer science; Business; Computer security; Psychology","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":[0.0004145313,0.0001624484,0.0001735928,0.00009273225,0.0003203039,0.00006498543,0.0002160911,0.00009931593,0.001933693],"category_scores_gemma":[0.0001231511,0.0001458561,0.0001138604,0.0002338504,0.0001002922,0.0003582482,0.00008816526,0.0002409627,0.00003291001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000250433,"about_ca_system_score_gemma":0.00003668707,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004487901,"about_ca_topic_score_gemma":0.000327677,"domain_scores_codex":[0.998562,0.0001621459,0.0004093129,0.0003239452,0.0002474884,0.0002950504],"domain_scores_gemma":[0.9993082,0.00006624476,0.0002477395,0.0002371055,0.00002154333,0.0001191511],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004757219,0.0004775195,0.08475701,0.0000133081,0.0002193587,0.00002568884,0.0004410955,0.5005723,0.0737362,0.00178982,0.2906371,0.04685484],"study_design_scores_gemma":[0.002161103,0.001137323,0.2001649,0.0001441273,0.0003599566,0.00019607,0.001852341,0.004677119,0.1200228,0.005098558,0.6633404,0.0008453095],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9597157,0.0000287133,0.02850328,0.00444731,0.001460821,0.0004865016,0.00003436144,0.00003877109,0.005284573],"genre_scores_gemma":[0.9547795,0.00007605315,0.001808537,0.0003755283,0.0001128464,0.00003634275,0.00003763111,0.00001017328,0.04276335],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4958952,"threshold_uncertainty_score":0.9989787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02452717818642953,"score_gpt":0.3087585267434468,"score_spread":0.2842313485570173,"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."}}