{"id":"W6920986229","doi":"10.6084/m9.figshare.26735313","title":"Additional file 1 of Beyond benchmarking and towards predictive models of dataset-specific single-cell RNA-seq pipeline performance","year":2024,"lang":"en","type":"article","venue":"Figshare","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; Lunenfeld-Tanenbaum Research Institute; Ontario Institute for Cancer Research; University of Toronto","funders":"","keywords":"Benchmarking; Pipeline (software); Data modeling","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":[0.004211109,0.002141249,0.001296995,0.002318442,0.001128272,0.002500808,0.00289043,0.001476204,0.5670507],"category_scores_gemma":[0.0258769,0.0007052096,0.001357822,0.003339498,0.0004945335,0.002290346,0.001649658,0.002011986,0.1953215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001160001,"about_ca_system_score_gemma":0.002047342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004223604,"about_ca_topic_score_gemma":0.009170996,"domain_scores_codex":[0.9982008,0.0003229929,0.0001848991,0.0007006236,0.0004278989,0.0001627203],"domain_scores_gemma":[0.9792317,0.01517244,0.0006518017,0.002161218,0.002342424,0.0004403952],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003231399,0.00007960477,0.002552473,0.002250088,0.0001238694,0.00005304586,0.00005246457,0.001864832,0.001244903,0.0007764109,0.9819919,0.008687343],"study_design_scores_gemma":[0.001767107,0.0004140246,0.02233456,0.0015317,0.0003821598,0.0004176417,0.0002695531,0.01599875,0.009466189,0.0175159,0.9296524,0.0002500292],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.0002492006,0.00003136878,0.001500973,0.0000538159,0.00004079234,0.0000408376,0.9949709,0.002549829,0.000562262],"genre_scores_gemma":[0.003284713,0.00005362081,0.005580271,0.0002389808,0.00003870178,0.0005761576,0.9860311,0.002287714,0.001908666],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5670507,"threshold_uncertainty_score":0.6175497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0275371241649037,"score_gpt":0.2123941654024467,"score_spread":0.184857041237543,"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."}}