{"id":"W4386745126","doi":"10.21203/rs.3.rs-3226465/v1","title":"Meso-scale geoacoustic seabed quantification","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Underwater Acoustics Research","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria; University of Calgary","funders":"Office of Naval Research; Alliance de recherche numérique du Canada; University of Waterloo; Simon Fraser University; Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Seabed; Geology; Scale (ratio); Oceanography; Geography; Cartography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001936039,0.0004827186,0.0003006381,0.000691817,0.0001561364,0.0004992009,0.0004151286,0.0004072608,0.002972997],"category_scores_gemma":[0.0007128973,0.0002729349,0.0002584348,0.0006825966,0.0001891045,0.0008574116,0.0007712447,0.0004236311,0.0009845603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000187563,"about_ca_system_score_gemma":0.0003610243,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004305255,"about_ca_topic_score_gemma":0.00632184,"domain_scores_codex":[0.9999144,0.00001102297,0.000003799525,0.00003172366,0.00002321194,0.00001579603],"domain_scores_gemma":[0.9998664,0.00002330393,0.00001484287,0.00004014232,0.00004111692,0.00001415536],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.000121188,0.0001198215,0.03228886,0.0001389419,0.0001250936,0.000116687,0.00009621435,0.7193682,0.06403603,0.003517115,0.003890262,0.1761816],"study_design_scores_gemma":[0.000004945742,0.00001104932,0.01224053,0.000005678016,0.000007464593,0.00001371894,0.00002444222,0.9831015,0.002594382,0.00131671,0.0006711718,0.000008323227],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4688421,0.0003133881,0.5145919,0.000290226,0.0001427939,0.00006024949,0.004242834,0.003159427,0.008357059],"genre_scores_gemma":[0.9308891,0.0001249692,0.06468418,0.00002685748,0.00003005526,0.00002461891,0.001506896,0.0001564895,0.002556859],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004305255,"threshold_uncertainty_score":0.009945631,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.165949896201092,"score_gpt":0.3946661021793543,"score_spread":0.2287162059782623,"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."}}