{"id":"W2795547764","doi":"","title":"Time-lapse Geophysical Data from a Stressed Environment","year":2015,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Geological Modeling and Analysis","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Geology; Geophysics; Remote sensing","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":[0.0004589582,0.0001600751,0.0002240887,0.00002955177,0.00009183485,0.00007127618,0.0005779104,0.00008779435,0.0002742943],"category_scores_gemma":[0.0003213344,0.0001238759,0.00004881641,0.00007143773,0.00006522473,0.0001603427,0.00007499939,0.0001894355,0.009041538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003912295,"about_ca_system_score_gemma":0.00002999901,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07990227,"about_ca_topic_score_gemma":0.007159803,"domain_scores_codex":[0.998373,0.00008497087,0.0002762218,0.0005203476,0.0004138099,0.0003315946],"domain_scores_gemma":[0.9986894,0.000255558,0.000115178,0.000589587,0.00002040785,0.0003298841],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005004059,0.0001456397,0.3348956,0.000005172678,0.00008693099,0.0001117086,0.0001839671,0.6402885,0.00008784088,7.672555e-7,0.005869977,0.01827384],"study_design_scores_gemma":[0.0003957809,0.00009852117,0.3429079,0.00003612846,0.00009846999,0.000002165495,0.0001795944,0.6478764,0.00003919962,0.0008488227,0.007184567,0.0003325024],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.990555,0.0003378293,0.00002538909,0.0004577462,0.00008802472,0.00004977801,0.0002346282,0.000072989,0.008178612],"genre_scores_gemma":[0.9946072,0.00002300683,0.00261759,0.0001620817,0.0003262681,4.203785e-7,0.001970411,0.000003825552,0.0002892003],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07274246,"threshold_uncertainty_score":0.99173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04798468308664329,"score_gpt":0.2275735608769552,"score_spread":0.1795888777903119,"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."}}