{"id":"W4403857947","doi":"10.1130/abs/2024am-403978","title":"THE VALUE OF 3D MODELS AND DERIVATIVE PRODUCTS TO SUPPORT EVIDENCE-BASED DECISION MAKING AND FACILITATE STAKEHOLDER COMMUNICATION","year":2024,"lang":"en","type":"article","venue":"Abstracts with programs - Geological Society of America","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Alberta Energy","funders":"","keywords":"Stakeholder; Value (mathematics); Computer science; Derivative (finance); Knowledge management; Management science; Business; Engineering; Machine learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03755036,0.0007553621,0.0008475189,0.01106053,0.0009409789,0.01539368,0.00197157,0.003735079,0.01930312],"category_scores_gemma":[0.2038992,0.0009728359,0.001719204,0.005778334,0.003685264,0.0107259,0.006246043,0.002824934,0.002175194],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003542493,"about_ca_system_score_gemma":0.005477625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007010325,"about_ca_topic_score_gemma":0.01109494,"domain_scores_codex":[0.9711946,0.01761333,0.002092375,0.0008742217,0.007815158,0.0004101795],"domain_scores_gemma":[0.7358389,0.2119905,0.01010444,0.01784616,0.02202776,0.002192215],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006815443,0.000202216,0.01844177,0.002317944,0.0004291773,0.0005672383,0.002161356,0.03061581,0.00142602,0.1406128,0.04712427,0.75542],"study_design_scores_gemma":[0.0003119237,0.0005430604,0.01890207,0.01050732,0.0006255645,0.001374152,0.004770367,0.141189,0.005423866,0.6155355,0.2001561,0.000661056],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.09043805,0.02719505,0.4977683,0.1912997,0.005052237,0.0009691307,0.009822289,0.003560837,0.1738945],"genre_scores_gemma":[0.615859,0.01217221,0.3593751,0.004463721,0.0008436532,0.0004844022,0.001972158,0.0004906196,0.004339035],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.03755036,"threshold_uncertainty_score":0.1985877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2092496041782471,"score_gpt":0.3269936495899074,"score_spread":0.1177440454116603,"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."}}