{"id":"W2327048247","doi":"10.1190/segam2012-1438.1","title":"3D inversion of DC/IP data using adaptive OcTree meshes","year":2012,"lang":"en","type":"article","venue":"","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Polygon mesh; Octree; Computer science; Inversion (geology); Computer graphics (images); Computational science; Computer vision; Geology","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":[],"consensus_categories":[],"category_scores_codex":[0.0003246173,0.0000781858,0.000106544,0.0001354308,0.00005309596,0.00003636554,0.00103693,0.00003793646,0.00001558987],"category_scores_gemma":[0.00001181067,0.00006754504,0.00002599832,0.0003990611,0.00003153713,0.001093631,0.00134136,0.00004201357,0.000002913368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001123555,"about_ca_system_score_gemma":0.00002931894,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001055277,"about_ca_topic_score_gemma":0.00000647975,"domain_scores_codex":[0.9992477,0.00004347751,0.0001627822,0.0002010635,0.000190854,0.0001541156],"domain_scores_gemma":[0.9989146,0.00004597786,0.00008662101,0.0008125599,0.00007740352,0.00006281199],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002472492,0.0001091604,0.004307606,0.00001126191,0.00001900213,5.364319e-7,0.0005119769,0.000005008102,0.0007122515,0.970291,0.00603536,0.01799436],"study_design_scores_gemma":[0.00007733083,0.00003822196,0.0005953574,0.00002182106,0.000005902266,0.000002777546,0.00001852749,0.977177,0.01579219,0.002614907,0.003538033,0.0001179099],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006302748,0.0001199883,0.9922433,0.00004721669,0.0002017282,0.0000705743,0.000003109153,0.0001466479,0.00086471],"genre_scores_gemma":[0.7138047,0.00002052559,0.2859477,0.0001429444,0.00004057102,5.465201e-7,0.000005103188,0.000003982997,0.00003392067],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.977172,"threshold_uncertainty_score":0.2754407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1358946931835681,"score_gpt":0.3414426434657691,"score_spread":0.205547950282201,"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."}}