{"id":"W3121258435","doi":"10.1177/0004563221992822","title":"Pneumatic tube validation: Reducing the need for donor samples by integrating a vial-embedded data logger","year":2021,"lang":"en","type":"article","venue":"Annals of Clinical Biochemistry International Journal of Laboratory Medicine","topic":"Clinical Laboratory Practices and Quality Control","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Tube (container); Data logger; Medicine; Biomedical engineering; Environmental science; Engineering; Computer science; Operating system; Mechanical engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.009377632,0.0002273302,0.001156551,0.00006280172,0.0000715667,0.00005268546,0.0009243567,0.0002348719,0.0004210504],"category_scores_gemma":[0.1000248,0.000145229,0.0003356338,0.0003250432,0.0004266041,0.0003160054,0.0001671491,0.0008017935,0.000002501512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002531005,"about_ca_system_score_gemma":0.001512458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001111344,"about_ca_topic_score_gemma":0.000002120943,"domain_scores_codex":[0.9944226,0.0004646655,0.00340765,0.0004082117,0.001078662,0.0002182057],"domain_scores_gemma":[0.9770612,0.009737578,0.003240856,0.0009281594,0.008685444,0.0003468374],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.006699033,0.002324793,0.007470042,0.0006393275,0.00523967,0.0002119296,0.0004817302,0.00001760871,0.4639325,0.0007376138,0.4782823,0.03396348],"study_design_scores_gemma":[0.01893716,0.0025854,0.001490927,0.005702618,0.002160222,0.0003662835,0.00729195,0.001690211,0.4898749,0.001011322,0.4682819,0.0006070714],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7062121,0.00488267,0.002370974,0.2823518,0.002419659,0.0003234487,0.001063073,0.00001895337,0.0003573056],"genre_scores_gemma":[0.9707302,0.001999684,0.003449478,0.0170348,0.0057387,0.000007639686,0.0007511018,0.00003243625,0.0002559198],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.265317,"threshold_uncertainty_score":0.9075561,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2780765285559251,"score_gpt":0.5254694107041182,"score_spread":0.2473928821481932,"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."}}