{"id":"W4405131267","doi":"10.1101/2024.12.04.626769","title":"Reporting quality of quantitative polymerase chain reaction (qPCR) methods in scientific publications","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Molecular Biology Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Polymerase chain reaction; Computational biology; Quality (philosophy); Real-time polymerase chain reaction; Business; Computer science; Chemistry; Biology; Biochemistry; Gene; Philosophy; Epistemology","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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.4022683,0.001493484,0.003749755,0.03388766,0.004108179,0.01726107,0.004275565,0.00444327,0.01195578],"category_scores_gemma":[0.7705104,0.00152969,0.002478946,0.03665526,0.005631416,0.008574112,0.008650256,0.003267448,0.004706373],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005140421,"about_ca_system_score_gemma":0.02510408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002252265,"about_ca_topic_score_gemma":0.001844102,"domain_scores_codex":[0.36102,0.2033922,0.2742277,0.02455471,0.1322465,0.004558819],"domain_scores_gemma":[0.06455249,0.5631846,0.1531203,0.06504509,0.1516222,0.002475325],"domain_codex":null,"domain_gemma":"reporting","domain_candidate":"reporting","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001456548,0.0002747049,0.1436961,0.163489,0.003021518,0.002371193,0.02690206,0.002180224,0.013148,0.0438703,0.128213,0.4713774],"study_design_scores_gemma":[0.0003272424,0.00043574,0.0707458,0.09417208,0.002768311,0.002005602,0.00824043,0.004116723,0.01787305,0.05879454,0.7397546,0.0007660044],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1312461,0.1422625,0.4147561,0.06209592,0.02575669,0.02226857,0.1327213,0.005481953,0.06341089],"genre_scores_gemma":[0.4620508,0.05816708,0.336714,0.01594433,0.007517783,0.04187806,0.06237038,0.00310837,0.01224924],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5977317,"threshold_uncertainty_score":0.7371097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05392150205408191,"score_gpt":0.3805886030310818,"score_spread":0.3266671009769999,"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."}}