{"id":"W2272228052","doi":"10.1190/tle35020126.1","title":"Introduction to this special section: Imaging/inversion: Estimating the earth model","year":2016,"lang":"en","type":"article","venue":"The Leading Edge","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Calgary Construction Association","funders":"","keywords":"Inversion (geology); Preprocessor; Geology; Geophysical imaging; Computer science; Seismic inversion; Property (philosophy); Special section; Section (typography); Geophysics; Seismology; Artificial intelligence; Geometry; Mathematics; Engineering","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":["insufficient_payload"],"category_scores_codex":[0.0006385655,0.0001093588,0.00009068253,0.00006267722,0.0005814042,0.00008243551,0.0003237584,0.00002724177,0.00239549],"category_scores_gemma":[0.0001081776,0.0000498524,0.00004584793,0.0001944268,0.0001379736,0.0002626939,0.0000281847,0.0001568961,0.002534094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000136915,"about_ca_system_score_gemma":0.00002672962,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00030228,"about_ca_topic_score_gemma":0.00002055077,"domain_scores_codex":[0.9991007,0.0000735356,0.0001308311,0.0002350469,0.0002124818,0.0002473957],"domain_scores_gemma":[0.9994034,0.0001314265,0.00005448838,0.0003149024,0.00003719689,0.0000586104],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001495384,0.000002065967,0.0007628519,0.000001858686,0.000003500423,7.418672e-7,0.0005174886,0.001419253,0.0003434385,0.00008944195,0.8224516,0.1743928],"study_design_scores_gemma":[0.0001087872,0.00003593108,0.0004068341,0.00003219846,0.00001380424,0.0000385658,0.0001111557,0.2730375,0.003426255,0.001614976,0.7210231,0.000150929],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1302659,0.0002391221,0.1404066,0.5274813,0.02592339,0.0008691183,0.00005094344,0.00131051,0.1734532],"genre_scores_gemma":[0.8488232,0.00003372574,0.01369801,0.01753487,0.05923636,0.000005655904,0.00001640054,0.00001918069,0.06063257],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7185574,"threshold_uncertainty_score":0.9985164,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0167120811534034,"score_gpt":0.2243342909732575,"score_spread":0.2076222098198541,"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."}}