{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002112968,0.002854898,0.00265664,0.005320957,0.001654061,0.005350252,0.003564007,0.003028851,0.6217269],"category_scores_gemma":[0.01060461,0.001812242,0.001837598,0.007417369,0.0007133693,0.002923396,0.002688671,0.002453038,0.6036694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001780529,"about_ca_system_score_gemma":0.003338869,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01093758,"about_ca_topic_score_gemma":0.0182734,"domain_scores_codex":[0.9981104,0.0003033141,0.0002710003,0.0006816544,0.0003157766,0.0003178444],"domain_scores_gemma":[0.9944713,0.002346073,0.0004342574,0.001241755,0.001120907,0.0003857797],"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":[0.00007313605,0.00002330159,0.0003173563,0.001441679,0.00002067315,0.000009138428,0.00002387188,0.0001270077,0.0002278456,0.0004904303,0.9946068,0.002638795],"study_design_scores_gemma":[0.0003900965,0.00003175154,0.001505227,0.0004898623,0.00003804916,0.00003362011,0.00007283251,0.0001696685,0.0006642812,0.002141203,0.9944247,0.0000387108],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000286658,0.00002865443,0.00006132681,0.00003568479,0.00001657961,0.00001305533,0.9985502,0.0004279248,0.0008378983],"genre_scores_gemma":[0.0003778227,0.00007672044,0.0005619994,0.0001612705,0.00001834313,0.0002171314,0.995308,0.0005509154,0.002727752],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3782731,"threshold_uncertainty_score":0,"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."}}