{"id":"W6930599162","doi":"10.5281/zenodo.14648370","title":"TCL38 PSet v1.1","year":2025,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Prenatal Screening and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; Princess Margaret Cancer Centre; University of Toronto","funders":"","keywords":"Epigenetics; Leukemia; Lymphoma; Cancer; Vorinostat","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":[0.0008955064,0.002446959,0.002077023,0.003094543,0.0007505646,0.002359542,0.003310836,0.002824475,0.04867757],"category_scores_gemma":[0.003979345,0.0006949996,0.001640718,0.0058273,0.0004384771,0.0009023091,0.001460273,0.001666707,0.0670073],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001360368,"about_ca_system_score_gemma":0.002053985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01785007,"about_ca_topic_score_gemma":0.02815491,"domain_scores_codex":[0.9990788,0.0001909895,0.000117168,0.0003127576,0.0001738593,0.0001264262],"domain_scores_gemma":[0.9989578,0.0003619215,0.0001222672,0.0002537563,0.0001791884,0.0001250436],"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":[0.0002371583,0.00003523967,0.001483435,0.001455345,0.0001290518,0.0001434755,0.00002895821,0.00146116,0.0005170968,0.0009362855,0.9895331,0.004039703],"study_design_scores_gemma":[0.0007363974,0.00005737594,0.004671195,0.0004050342,0.0001576245,0.0004431128,0.00004986962,0.001556358,0.0007973734,0.002421718,0.988654,0.00005003434],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000258342,0.000160218,0.0001214993,0.000051582,0.0000179614,0.000009526899,0.998634,0.0003269979,0.0004197995],"genre_scores_gemma":[0.0004654312,0.00006557131,0.0001841632,0.0000446302,0.000004977142,0.000046051,0.9988512,0.00005978101,0.0002781777],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04867757,"threshold_uncertainty_score":0.1628427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03118107336356099,"score_gpt":0.2792148209755144,"score_spread":0.2480337476119534,"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."}}