{"id":"W2309505246","doi":"10.14288/1.0072252","title":"Analysis of water cooling process of steel strips on runout table","year":2011,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Engineering Applied Research","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"STRIPS; Table (database); Process (computing); Water cooling; Environmental science; Engineering drawing; Engineering; Mechanical engineering; Materials science; Computer science; Composite material; Data mining","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002219573,0.00003952547,0.0003155229,0.0001819207,0.00004312913,0.00001014466,0.0002839041,0.0000885705,0.0001800703],"category_scores_gemma":[0.00001131652,0.0001155073,0.00009622932,0.0005982096,0.00009206552,0.00009454759,0.00004409086,0.0001634136,0.00000413207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004839747,"about_ca_system_score_gemma":0.00002420218,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01392131,"about_ca_topic_score_gemma":0.008530678,"domain_scores_codex":[0.9992309,0.00001478762,0.0001278977,0.000154513,0.0002227255,0.0002491342],"domain_scores_gemma":[0.9994991,0.00002675383,0.00003639883,0.0002258275,0.0001392395,0.00007262434],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0001507144,0.0008769429,0.08277503,0.004493494,0.005336878,0.0002435223,0.0122303,0.6561314,0.1165105,0.00001981836,0.000926311,0.120305],"study_design_scores_gemma":[0.0004664497,0.00006881673,0.9534979,0.0001352629,0.0002474538,0.000002840925,0.001517216,0.04077157,0.003086787,0.00002246386,0.00001753252,0.0001657225],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948681,0.0000413159,0.001545833,9.378992e-7,0.00002582644,0.0001007322,0.0001034135,0.00006830295,0.003245539],"genre_scores_gemma":[0.9993344,0.00003952828,0.0004476356,0.000001017614,0.000005182063,4.98229e-7,0.0000126242,0.00001673058,0.0001423775],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8707228,"threshold_uncertainty_score":0.9926451,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01115129888971174,"score_gpt":0.1740762401548311,"score_spread":0.1629249412651194,"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."}}