{"id":"W1985385412","doi":"10.4043/18011-ms","title":"Scientific Ocean Drilling: Characterizing and Sampling Methane Hydrates","year":2006,"lang":"en","type":"article","venue":"Offshore Technology Conference","topic":"Methane Hydrates and Related Phenomena","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Geological Survey of Canada","funders":"","keywords":"Methane; Drilling; Sampling (signal processing); Petroleum engineering; Geology; Scientific drilling; Clathrate hydrate; Oceanography; Computer science; Environmental science; Earth science; Hydrate; Chemistry; Engineering; Mechanical engineering; Telecommunications","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":[0.001191484,0.0002898534,0.0001518207,0.001304641,0.0004349337,0.0004366923,0.0005439426,0.0004429171,0.0004380815],"category_scores_gemma":[0.0008596093,0.0002007594,0.0001375657,0.001533342,0.0003281354,0.0003004771,0.0005249357,0.0002223108,0.0002059184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003693792,"about_ca_system_score_gemma":0.001178868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009668051,"about_ca_topic_score_gemma":0.02329032,"domain_scores_codex":[0.9993662,0.0001139255,0.00002837533,0.00008221415,0.000364092,0.00004517229],"domain_scores_gemma":[0.9995661,0.00007265044,0.0001138716,0.00004030854,0.0001636298,0.00004337643],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0003463429,0.0002102533,0.3099028,0.0005332709,0.00007175872,0.0002435543,0.0003241044,0.008649714,0.3532562,0.0009339459,0.005678905,0.3198492],"study_design_scores_gemma":[0.0001247184,0.001243092,0.615725,0.0002336069,0.00008787979,0.0008423859,0.001173334,0.03422003,0.2818248,0.001270752,0.06316508,0.00008937204],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8860356,0.002679631,0.09095944,0.0007803215,0.0001122165,0.0006420464,0.00365882,0.0008124389,0.01431963],"genre_scores_gemma":[0.7966545,0.001867907,0.1957005,0.0001912365,0.00006117184,0.0003873576,0.002566915,0.00006467248,0.002505796],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009668051,"threshold_uncertainty_score":0.01922357,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01685692347006978,"score_gpt":0.2265593255718014,"score_spread":0.2097024021017316,"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."}}