{"id":"W6966944677","doi":"10.48380/dggv-g2qs-zq28","title":"Time-lapse imagery of a highly active submarine channel and its implications for seafloor geohazards","year":2020,"lang":"en","type":"other","venue":"dggv-e-publications","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; University of Calgary","funders":"","keywords":"Seafloor spreading; Submarine; Channel (broadcasting); Submarine pipeline; Submarine canyon; Canyon; Seabed; Submarine landslide","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0001073744,0.00008338297,0.00005051689,0.0006428708,0.0001228392,0.0003509466,0.0001121384,0.0002423375,0.003992255],"category_scores_gemma":[0.0002455387,0.00006588418,0.00006154962,0.0005426689,0.00009817108,0.0001969278,0.0001916592,0.0001719218,0.0009453731],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001086233,"about_ca_system_score_gemma":0.0001477991,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005098652,"about_ca_topic_score_gemma":0.01635122,"domain_scores_codex":[0.9999734,0.000001722414,9.239856e-7,0.000006250321,0.00001101715,0.000006735039],"domain_scores_gemma":[0.9998789,0.00001810994,0.00001626278,0.0000132907,0.00003748236,0.00003605847],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0008184006,0.0003246964,0.1519736,0.0004127447,0.00009415947,0.00233312,0.001061294,0.01648443,0.3086332,0.002643313,0.062001,0.45322],"study_design_scores_gemma":[0.0000276776,0.0001321704,0.8860511,0.0001378668,0.00005160232,0.001619826,0.0009031924,0.04185919,0.01947351,0.001025232,0.04867647,0.0000421638],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.938758,0.0008075988,0.01263646,0.0006323289,0.0001663821,0.00005962369,0.01362188,0.001089908,0.03222784],"genre_scores_gemma":[0.9635265,0.000732776,0.01916531,0.000102471,0.00008497382,0.00002581073,0.008914247,0.0001780599,0.007269816],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005098652,"threshold_uncertainty_score":0.01335543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02763979986056222,"score_gpt":0.2873327854577106,"score_spread":0.2596929855971484,"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."}}