{"id":"W2077726274","doi":"10.1016/j.marpetgeo.2013.04.011","title":"Seismic facies analyses as aid in regional gas hydrate assessments. Part-I: Classification analyses","year":2013,"lang":"en","type":"article","venue":"Marine and Petroleum Geology","topic":"Methane Hydrates and Related Phenomena","field":"Environmental Science","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria; Geological Survey of Canada; Natural Resources Canada","funders":"","keywords":"Facies; Geology; Clathrate hydrate; Lithology; Petrology; Natural gas; Seismic attribute; Regional geology; Sedimentary depositional environment; Hydrate; Drilling; Geochemistry; Petroleum engineering; Structural basin; Geomorphology; Paleontology; Tectonics; Volcanism","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":[0.0001863554,0.0001920701,0.0002816802,0.000134519,0.0001024117,0.00003924645,0.0001570845,0.0001293398,0.01038681],"category_scores_gemma":[0.0000167557,0.0001507313,0.00005366185,0.0002662896,0.0002649117,0.0002156767,0.0002442993,0.0002277968,0.000938022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005203514,"about_ca_system_score_gemma":0.0000135049,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01118425,"about_ca_topic_score_gemma":0.000765343,"domain_scores_codex":[0.9985286,0.0001807438,0.000333207,0.0004216599,0.0001711268,0.0003646907],"domain_scores_gemma":[0.9994181,0.00008190119,0.0001371412,0.0002362155,0.00001090123,0.0001157219],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003993793,0.0001255705,0.955579,0.00001039604,0.00008446711,0.00001422445,0.000120286,0.01692531,0.01171846,0.000264498,0.0020773,0.01304053],"study_design_scores_gemma":[0.0008550112,0.0002920501,0.7969452,0.000007439633,0.00006360772,0.00004338792,0.0003680725,0.1361118,0.0003629245,0.01351569,0.05107127,0.0003636691],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.962023,0.0001716042,0.00007986305,0.002026991,0.0000712288,0.0001017416,0.000001311844,0.00002321883,0.03550109],"genre_scores_gemma":[0.9891775,0.001058835,0.0002303049,0.0006651917,0.00003701067,0.00005369492,0.00008910886,0.00001022388,0.008678191],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1586339,"threshold_uncertainty_score":0.9998398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05495486915446329,"score_gpt":0.3194020026146016,"score_spread":0.2644471334601383,"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."}}