{"id":"W4283519535","doi":"10.1306/02072219107","title":"How did the world’s largest submarine fan in the Bay of Bengal grow and evolve at the subfan scale?","year":2022,"lang":"en","type":"article","venue":"AAPG Bulletin","topic":"Geological and Geophysical Studies","field":"Earth and Planetary Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Petro-Canada","funders":"","keywords":"BENGAL; Bay; Geology; Submarine; Scale (ratio); Oceanography; Geography; Cartography","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":[0.000334488,0.0001833023,0.00013038,0.0006026022,0.00106403,0.002260466,0.0003425964,0.0003761372,0.002808426],"category_scores_gemma":[0.0008804124,0.0001057462,0.0001264757,0.0007946683,0.0009814678,0.001497395,0.0007287918,0.0003830978,0.0004135072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003542204,"about_ca_system_score_gemma":0.00121857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1057291,"about_ca_topic_score_gemma":0.1459786,"domain_scores_codex":[0.9998097,0.00002484591,0.00000434558,0.00003814904,0.00002725375,0.00009570859],"domain_scores_gemma":[0.9997762,0.00001798757,0.00005277239,0.00001510758,0.00007219477,0.00006569046],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002464867,0.00004707728,0.7932577,0.0001686278,0.00008310596,0.004899045,0.02999461,0.001999655,0.01846591,0.01907826,0.004460857,0.1272986],"study_design_scores_gemma":[0.000004319003,0.00005761,0.9060683,0.0000554584,0.00002273697,0.0005781401,0.03425942,0.001351488,0.002135744,0.002218721,0.05320752,0.00004046079],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9880058,0.0004232205,0.0002058495,0.001603873,0.00002521646,0.000008046685,0.0001677093,0.000009789449,0.009550511],"genre_scores_gemma":[0.9985558,0.0001916544,0.00007609699,0.00004952864,0.000007314418,0.000001524631,0.00003899719,0.000004062325,0.001075014],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1057291,"threshold_uncertainty_score":0.2102273,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008813245295703138,"score_gpt":0.170496465365215,"score_spread":0.1616832200695119,"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."}}