{"id":"W2784820820","doi":"","title":"TransCanada's Use of Pipeline Simulations to Support Short Notice Services","year":2007,"lang":"en","type":"article","venue":"PSIG Annual Meeting","topic":"Radiology practices and education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"TransCanada (Canada)","funders":"","keywords":"Notice; Pipeline (software); Computer science; Business; Political science; Operating system","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.001277763,0.0005051668,0.0002153915,0.0005515745,0.0007659734,0.001549406,0.001231836,0.0006567827,0.02157842],"category_scores_gemma":[0.006266686,0.0002996726,0.000270781,0.000421753,0.000345907,0.001251221,0.001342949,0.0008931098,0.002809492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001291436,"about_ca_system_score_gemma":0.002173265,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01237257,"about_ca_topic_score_gemma":0.01395072,"domain_scores_codex":[0.9992933,0.0002478923,0.00004022006,0.0001322496,0.0001942521,0.00009189542],"domain_scores_gemma":[0.9965559,0.00128975,0.0001066664,0.0007178881,0.0008704751,0.0004593688],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003488478,0.002239517,0.02836642,0.0002549026,0.0001078263,0.00129316,0.002832433,0.111211,0.03434074,0.02238141,0.1429995,0.6504846],"study_design_scores_gemma":[0.0006074146,0.0007777265,0.006648584,0.00008631855,0.00006440211,0.0008256054,0.001036485,0.6407706,0.0218127,0.0063279,0.3208999,0.0001423989],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.376623,0.0002160215,0.2481681,0.003150024,0.001089886,0.00148663,0.001850352,0.07542327,0.2919927],"genre_scores_gemma":[0.8449623,0.000128088,0.1173214,0.0002878533,0.00004638894,0.000219877,0.001679616,0.001863765,0.0334907],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02157842,"threshold_uncertainty_score":0.07218695,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0429688568362267,"score_gpt":0.3484372368710336,"score_spread":0.3054683800348069,"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."}}