{"id":"W6910480303","doi":"10.48331/scielodata.96uynu/pomo1x","title":"qPCR.tab","year":2023,"lang":"en","type":"dataset","venue":"SciELO - Scientific Electronic Library Online Dataverse","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Process (computing); Identification (biology); Product (mathematics)","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":["metaepi_narrow","sts","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","insufficient_payload"],"category_scores_codex":[0.00281412,0.001735964,0.00144017,0.003734512,0.00161172,0.003493314,0.009773348,0.0009964762,0.02023591],"category_scores_gemma":[0.0006521369,0.001704568,0.0006773801,0.01172125,0.002278655,0.006415284,0.005060142,0.003803111,0.578167],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000692351,"about_ca_system_score_gemma":0.009684345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003697985,"about_ca_topic_score_gemma":0.002399697,"domain_scores_codex":[0.9844344,0.0006047385,0.00169118,0.004964371,0.00340969,0.00489559],"domain_scores_gemma":[0.9887543,0.0003794722,0.00107018,0.008565264,0.0001849644,0.001045768],"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":[0.0001025774,0.0007236589,0.000005034807,0.0002170229,0.0002528273,0.0002970409,0.0000227834,0.00002898113,0.0002229528,0.0003079214,0.9975977,0.0002214988],"study_design_scores_gemma":[0.001118126,0.0001837987,0.00002121612,0.0002629826,0.0003412532,0.00007295239,0.0001233262,0.0004559768,0.0001782197,0.00157815,0.9938304,0.001833631],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004194797,0.0002304829,0.000001441877,0.0003868247,0.009545648,0.001360648,0.9852874,0.00256787,0.00020015],"genre_scores_gemma":[0.000004418201,0.0006564836,0.0002925287,0.0005234054,0.002316708,0.00008070237,0.9422488,0.00054436,0.05333259],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5579311,"threshold_uncertainty_score":0.999688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02128388205770855,"score_gpt":0.2750883899660872,"score_spread":0.2538045079083787,"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."}}