{"id":"W4396533179","doi":"10.4043/35435-ms","title":"The Canada Coastal Zone Information System for Model-Based Projections of Future Metocean Parameters from Coupled Atmosphere-Ocean Models Under Different Greenhouse Gas Emission Scenarios for Offshore Marine Energy Development in Canada","year":2024,"lang":"en","type":"article","venue":"Offshore Technology Conference","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"ASL Environmental Sciences (Canada)","funders":"","keywords":"Environmental science; Atmosphere (unit); Greenhouse gas; Submarine pipeline; Oceanography; Meteorology; Geology; Geography","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":[0.001774453,0.001295472,0.000815046,0.00452304,0.002584218,0.004011907,0.002943092,0.001268923,0.02560282],"category_scores_gemma":[0.007332698,0.0008492408,0.0009740453,0.01054602,0.000567631,0.002042423,0.001885954,0.001539856,0.006740551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03534248,"about_ca_system_score_gemma":0.1078137,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9869621,"about_ca_topic_score_gemma":0.9855421,"domain_scores_codex":[0.9989154,0.00007458725,0.00007917111,0.0001212338,0.0006377958,0.0001717862],"domain_scores_gemma":[0.9932072,0.0004053941,0.0002629846,0.0006574481,0.004824218,0.0006428417],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000309324,0.00008920479,0.02165026,0.0005748742,0.0002804795,0.0003127594,0.0004736549,0.08899499,0.001739241,0.025521,0.7294835,0.1305706],"study_design_scores_gemma":[0.0002729458,0.00002897804,0.02796614,0.0006893885,0.0001633357,0.00007134069,0.0006790437,0.2140075,0.002387936,0.008489739,0.7448132,0.000430551],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.01525568,0.001127442,0.03422503,0.002006109,0.0002759136,0.0006002142,0.8618159,0.01285244,0.0718413],"genre_scores_gemma":[0.1054335,0.00274702,0.1036229,0.0004987214,0.00005190419,0.000680942,0.7671734,0.001765776,0.01802578],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03534248,"threshold_uncertainty_score":0.2564289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007512238559974906,"score_gpt":0.1784203025482418,"score_spread":0.1709080639882669,"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."}}