{"id":"W2566229973","doi":"","title":"Using AVO and LMR Analysis with DHI and Flat-Spot Calibration to Mitigate Reservoir Risk at Stonehouse, Offshore Nova Scotia","year":2013,"lang":"en","type":"article","venue":"","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geology; Submarine pipeline; Amplitude versus offset; Porosity; Inversion (geology); Nova scotia; Lithology; Amplitude; Drilling; Offset (computer science); Hydrocarbon exploration; Petroleum engineering; Mineralogy; Seismology; Petrology; Geomorphology; Geotechnical engineering; Structural basin; Engineering; Oceanography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004022765,0.0002609344,0.0001725689,0.0008988356,0.0004512321,0.0005635252,0.0003704339,0.0002089193,0.000909471],"category_scores_gemma":[0.001331867,0.0001648504,0.000134742,0.0007280036,0.0003109127,0.0002717429,0.0004911038,0.0001906208,0.0002583444],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001023408,"about_ca_system_score_gemma":0.002336364,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.349475,"about_ca_topic_score_gemma":0.6127368,"domain_scores_codex":[0.9997461,0.00003510687,0.00001449577,0.00005124692,0.00009352988,0.00005935354],"domain_scores_gemma":[0.9996141,0.00006295197,0.00006714675,0.00003111487,0.000178079,0.0000467049],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006088646,0.0001918266,0.6735728,0.0001218134,0.0001130968,0.001024952,0.001001895,0.04984728,0.09342221,0.0007711778,0.002136613,0.1771875],"study_design_scores_gemma":[0.00006699796,0.00007948795,0.8780804,0.00002972013,0.00003499417,0.0001441506,0.000827584,0.1067089,0.01145662,0.0002769781,0.002251798,0.00004238512],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9872169,0.00005174498,0.006436636,0.0001130488,0.0000146231,0.00004465348,0.0005232387,0.0002635728,0.005335563],"genre_scores_gemma":[0.9935459,0.00002163919,0.005053636,0.00002150891,0.000002635544,0.000009763746,0.0002537812,0.00002497796,0.001066128],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.650525,"threshold_uncertainty_score":0.6948817,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02121434214519022,"score_gpt":0.2275890891093509,"score_spread":0.2063747469641607,"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."}}