{"id":"W2110855170","doi":"10.1190/int-2013-0130.1","title":"Automatic approaches for seismic to well tying","year":2014,"lang":"en","type":"article","venue":"Interpretation","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Lawrence Berkeley National Laboratory","keywords":"Tying; Computer science; Metric (unit); Similarity (geometry); Process (computing); Task (project management); Dynamic time warping; TRACE (psycholinguistics); Measure (data warehouse); Matching (statistics); Artificial intelligence; Subjectivity; Data mining; Pattern recognition (psychology); Computer vision; Image (mathematics); Mathematics; Engineering; Programming language","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":[0.001259294,0.001208722,0.0007147092,0.002764975,0.0007545628,0.001604544,0.001622395,0.001091323,0.005804466],"category_scores_gemma":[0.005273189,0.0006525515,0.0007417232,0.001554292,0.0009818545,0.001186503,0.001517058,0.001281747,0.001329622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006130292,"about_ca_system_score_gemma":0.001176058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002951191,"about_ca_topic_score_gemma":0.004223693,"domain_scores_codex":[0.9987848,0.000375877,0.0000745881,0.0002742668,0.0003966604,0.00009391853],"domain_scores_gemma":[0.9967952,0.001462255,0.0003939684,0.0006478149,0.0006044178,0.00009631224],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002899574,0.000183856,0.001454847,0.0002597747,0.00008179304,0.0001916964,0.0005226023,0.1693053,0.1077681,0.01150101,0.002326123,0.706115],"study_design_scores_gemma":[0.00002059056,0.00005171531,0.001082032,0.00001057462,0.00001498239,0.000103796,0.0001258897,0.9532918,0.03534108,0.006707277,0.00321924,0.00003087871],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0152219,0.00003972738,0.9812858,0.000043669,0.00001713441,0.00005292821,0.00006600926,0.002529482,0.0007433681],"genre_scores_gemma":[0.2470623,0.0000607988,0.7506506,0.00003059653,0.00003205277,0.00008662284,0.0002912311,0.0005236421,0.001262153],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005804466,"threshold_uncertainty_score":0.01941794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02222948568194331,"score_gpt":0.2340972728863107,"score_spread":0.2118677872043674,"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."}}