{"id":"W6930949167","doi":"10.5281/zenodo.15832651","title":"Distributed Biomarker Discovery Pipeline","year":2025,"lang":"en","type":"preprint","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre","funders":"","keywords":"Pipeline (software); SPARK (programming language); Multivariable calculus; Pipeline transport; Big data; Key (lock); Predictive modelling","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":[],"consensus_categories":[],"category_scores_codex":[0.003027294,0.001456374,0.001650085,0.001763691,0.0005201205,0.003118698,0.002680496,0.0009665097,0.02763973],"category_scores_gemma":[0.009510395,0.0007383167,0.001670575,0.001932711,0.0004251123,0.001549593,0.002754864,0.001984115,0.02612405],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001024086,"about_ca_system_score_gemma":0.002917077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003184066,"about_ca_topic_score_gemma":0.003176375,"domain_scores_codex":[0.9984803,0.0002436455,0.0001185731,0.0005679863,0.0004712797,0.0001183501],"domain_scores_gemma":[0.9976071,0.0007266107,0.00009097722,0.0009646862,0.0004629343,0.0001476323],"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":[0.001818769,0.0002170968,0.004928426,0.0008881368,0.0004645586,0.0003386941,0.0001135102,0.04923417,0.01014743,0.04219453,0.6745644,0.2150901],"study_design_scores_gemma":[0.0008585999,0.0001221042,0.002272542,0.00007538847,0.00009858246,0.0003766876,0.00005972604,0.3797066,0.01089731,0.1810214,0.4244236,0.00008760065],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005258448,0.001011353,0.5796891,0.002385569,0.0004834797,0.0007045576,0.2506864,0.1492223,0.01055866],"genre_scores_gemma":[0.0794476,0.001025016,0.3576083,0.00169051,0.0003024821,0.001897627,0.5363677,0.008745951,0.01291474],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02763973,"threshold_uncertainty_score":0.09246415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1316222760555739,"score_gpt":0.3736416402971227,"score_spread":0.2420193642415488,"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."}}