{"id":"W2078779307","doi":"10.1109/oceanssyd.2010.5603607","title":"The assessment and evolution of offshore gas hydrate deposits using seafloor controlled source electromagnetic methodology","year":2010,"lang":"en","type":"article","venue":"OCEANS'10 IEEE SYDNEY","topic":"Methane Hydrates and Related Phenomena","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Submarine pipeline; Seafloor spreading; Geology; Petroleum engineering; Clathrate hydrate; Electromagnetic heating; Marine engineering; Oceanography; Seabed; Hydrate; Engineering; Electrical engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001432305,0.0002110745,0.0003775399,0.0000447596,0.0003417028,0.00003798255,0.0002573934,0.0001778563,0.0003500804],"category_scores_gemma":[0.0001002421,0.0001376077,0.00008860099,0.0002341144,0.0004476694,0.00008643961,0.00008993335,0.0004360654,0.00002227234],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009904071,"about_ca_system_score_gemma":0.00005689785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001914345,"about_ca_topic_score_gemma":0.0001965017,"domain_scores_codex":[0.9979675,0.000513245,0.0004095334,0.0003556353,0.0003046702,0.0004494399],"domain_scores_gemma":[0.998754,0.0004486303,0.0002569909,0.0003450672,0.00002647995,0.0001688517],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002011439,0.00006897683,0.009445042,0.00001343338,0.0000897405,0.000004188423,0.0002446618,0.001844316,0.9827914,0.0004773394,0.0002680409,0.004551739],"study_design_scores_gemma":[0.01955099,0.00329108,0.1274413,0.0001326263,0.001884991,0.0007216359,0.001179764,0.6905569,0.1202361,0.01986621,0.01287245,0.002265873],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9914085,0.0003775291,0.003417753,0.0003117785,0.0004020769,0.0004593561,0.000002370361,0.00002476706,0.003595889],"genre_scores_gemma":[0.9894029,0.0001206598,0.008876187,0.00005461242,0.000064566,0.00001265191,0.000002547711,0.00002508839,0.001440772],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8625553,"threshold_uncertainty_score":0.5611479,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01538853876740206,"score_gpt":0.2647589916056325,"score_spread":0.2493704528382304,"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."}}