{"id":"W6920999758","doi":"10.6084/m9.figshare.22671452.v1","title":"Additional file 3 of Size matters: the impact of nucleus size on results from spatial transcriptomics","year":2023,"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":"University of Toronto; University Health Network","funders":"","keywords":"Consistency (knowledge bases); Cluster analysis; Pattern recognition (psychology); File size; Hot spot (computer programming); Cell size","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":[0.003676776,0.002230935,0.002074667,0.003261902,0.001768183,0.003631391,0.002857069,0.002044162,0.8703561],"category_scores_gemma":[0.04665171,0.001144211,0.001781216,0.004048214,0.0006624995,0.003231758,0.002141659,0.001797868,0.2581697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001306125,"about_ca_system_score_gemma":0.002430283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006889814,"about_ca_topic_score_gemma":0.01060113,"domain_scores_codex":[0.998142,0.0002738258,0.0002484923,0.000473315,0.0006038591,0.0002584966],"domain_scores_gemma":[0.9463114,0.04324347,0.001572637,0.00297416,0.005089158,0.0008091273],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004678225,0.00009776304,0.002634109,0.003395198,0.00009622232,0.0001239177,0.0001080668,0.0006561967,0.0006854565,0.000703217,0.9840869,0.006945104],"study_design_scores_gemma":[0.00797616,0.0004521255,0.04948197,0.004059872,0.0005194274,0.001438604,0.0008888944,0.006628759,0.007165877,0.02295632,0.8978408,0.0005912423],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.0002211934,0.00002312625,0.0009414881,0.000138489,0.00006964521,0.00006244427,0.9957911,0.002019359,0.0007331002],"genre_scores_gemma":[0.01060302,0.0001582893,0.01126505,0.001021282,0.000204985,0.001896007,0.9558524,0.009769853,0.009228989],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8703561,"threshold_uncertainty_score":0.1849213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02313303011453253,"score_gpt":0.2409784092919099,"score_spread":0.2178453791773774,"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."}}