{"id":"W2048922440","doi":"10.1016/j.egypro.2011.02.294","title":"10+ years of the IEA-GHG Weyburn-Midale CO2 monitoring and storage project: Successes and lessons learned from multiple hydrogeological investigations","year":2011,"lang":"en","type":"article","venue":"Energy Procedia","topic":"CO2 Sequestration and Geologic Interactions","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Petroleum Technology Research Centre; University of Alberta","funders":"","keywords":"Hydrogeology; Environmental science; Groundwater; Petroleum engineering; Mining engineering; Environmental engineering; Waste management; Engineering; Geotechnical engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000622047,0.00008136477,0.00008737766,0.0000171497,0.0001306932,0.0000157403,0.000119922,0.00006665028,0.0008539423],"category_scores_gemma":[0.0002402869,0.00006302085,0.00002113793,0.0001334187,0.0004449799,0.0001562095,0.0001612174,0.00009654651,0.00001426676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001788053,"about_ca_system_score_gemma":0.00002094602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004535898,"about_ca_topic_score_gemma":0.001298998,"domain_scores_codex":[0.9993815,0.00004547555,0.0001303728,0.0002153707,0.0001118246,0.0001154085],"domain_scores_gemma":[0.9996187,0.0001041116,0.00008070788,0.0001314744,0.00001196867,0.0000530414],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007534926,0.0002989479,0.9290556,0.00001588566,0.00004880042,0.00001261953,0.008924169,0.0007128579,0.03674396,0.005769967,0.001167932,0.01717389],"study_design_scores_gemma":[0.0004045773,0.0001240939,0.9159124,0.00003501573,0.00003396258,0.0000144137,0.001066916,0.001427686,0.04153428,0.008293246,0.03090745,0.000245895],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939566,0.00006452545,0.0000261468,0.0003789344,0.00007870654,0.00007020148,0.000009804161,0.00002990403,0.0053852],"genre_scores_gemma":[0.9971884,0.00007421933,0.0008029042,0.00003712825,0.00002813901,0.00002862439,0.000004869967,0.000004962879,0.001830792],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02973952,"threshold_uncertainty_score":0.9350069,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05886035999178602,"score_gpt":0.2626705065048305,"score_spread":0.2038101465130445,"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."}}