{"id":"W2141385512","doi":"10.7901/2169-3358-2005-1-671","title":"OIL COMPOSITION AND PROPERTY DATABASE FOR OIL SPILL MODELING","year":2005,"lang":"en","type":"article","venue":"International Oil Spill Conference Proceedings","topic":"Oil Spill Detection and Mitigation","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Database; Composition (language); Petroleum; Environmental science; Oil spill; Computer science; Environmental protection; Chemistry","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":[0.001330772,0.00110424,0.0009389678,0.002878876,0.0005524026,0.001870307,0.003624336,0.001117012,0.01543019],"category_scores_gemma":[0.004654631,0.0006025002,0.001252485,0.003322395,0.0002672776,0.002614051,0.001453501,0.001093698,0.007773677],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00106392,"about_ca_system_score_gemma":0.001879725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01229727,"about_ca_topic_score_gemma":0.01145898,"domain_scores_codex":[0.9992819,0.00009457654,0.0001258579,0.0001334663,0.0003206793,0.0000434793],"domain_scores_gemma":[0.9982128,0.0004312889,0.0001422252,0.0005852644,0.000535891,0.00009259733],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001027706,0.0005876027,0.01584428,0.001960265,0.0004424789,0.00128763,0.0002364594,0.3790526,0.009714114,0.05768704,0.3559596,0.1762003],"study_design_scores_gemma":[0.0002362991,0.00008916411,0.002778515,0.0001706662,0.0001022537,0.0002598666,0.00008596577,0.6260475,0.009474709,0.02117907,0.3394779,0.00009804498],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.02660187,0.001282434,0.3134202,0.0009095902,0.0002324372,0.001135836,0.5586149,0.07227159,0.0255312],"genre_scores_gemma":[0.119532,0.001312955,0.1861622,0.0002865921,0.00005140176,0.0012392,0.6819103,0.002287381,0.007218003],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01543019,"threshold_uncertainty_score":0.05161911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02792860779453172,"score_gpt":0.2548979804512706,"score_spread":0.2269693726567389,"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."}}