{"id":"W7067478186","doi":"","title":"Liquid Argon HEC Wheel Assembly Database","year":2006,"lang":"en","type":"other","venue":"CERN Document Server (European Organization for Nuclear Research)","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"TRIUMF","funders":"","keywords":"Table (database); Listing (finance); Set (abstract data type); Conjunction (astronomy); Feedthrough","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":[0.001888452,0.001535961,0.001623948,0.004857355,0.001239611,0.00465694,0.004098557,0.001105396,0.2056127],"category_scores_gemma":[0.005401492,0.000757599,0.0009018712,0.005165663,0.0002742065,0.003548474,0.00173304,0.001334757,0.2068149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001375375,"about_ca_system_score_gemma":0.002326888,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008554501,"about_ca_topic_score_gemma":0.005392395,"domain_scores_codex":[0.9970943,0.0002474248,0.0003228084,0.000387989,0.001754886,0.0001926381],"domain_scores_gemma":[0.995595,0.0004810337,0.0002758543,0.001707124,0.001781486,0.00015954],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000471914,0.0001043075,0.001073762,0.00039394,0.00003489201,0.0001690309,0.00006346037,0.00164643,0.002946355,0.007733464,0.9017441,0.08361831],"study_design_scores_gemma":[0.00006919588,0.00003067086,0.0009132301,0.00003907841,0.00001672937,0.0001833242,0.0000355755,0.005314909,0.006124665,0.00242009,0.9848103,0.0000422573],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003870626,0.0007854087,0.07557657,0.0005262877,0.0002955539,0.000540029,0.6333393,0.165341,0.1197252],"genre_scores_gemma":[0.01135833,0.0005346094,0.02334231,0.0002519317,0.00008814114,0.000445325,0.9133304,0.008687417,0.04196158],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2056127,"threshold_uncertainty_score":0.687843,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08634453752449356,"score_gpt":0.3501573272095811,"score_spread":0.2638127896850875,"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."}}