{"id":"W6958410365","doi":"10.6084/m9.figshare.22671446","title":"Additional file 1 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":"Cluster analysis; Consistency (knowledge bases); Pattern recognition (psychology); Cluster (spacecraft); 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":[0.003631219,0.002144999,0.002292295,0.003008626,0.001729317,0.003364374,0.003319869,0.002029036,0.8798087],"category_scores_gemma":[0.03702695,0.001348763,0.001641011,0.00414543,0.0005993387,0.00320359,0.002002682,0.001952138,0.2696294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00130928,"about_ca_system_score_gemma":0.002767358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004926562,"about_ca_topic_score_gemma":0.008063879,"domain_scores_codex":[0.9982185,0.0002870051,0.0002412726,0.0004205288,0.0005778454,0.000254825],"domain_scores_gemma":[0.9622232,0.02940744,0.001270203,0.002589201,0.003703306,0.0008065786],"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":[0.0005784655,0.0001351956,0.00220293,0.004764574,0.00009388237,0.0001589185,0.0001166249,0.0007353716,0.001205284,0.0009102095,0.9784994,0.01059898],"study_design_scores_gemma":[0.008215304,0.0007010149,0.04179015,0.003974549,0.0005015509,0.001724969,0.0006990875,0.00783616,0.01023826,0.02058849,0.9031013,0.0006291229],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.0003111594,0.00003866074,0.001649575,0.0001730306,0.0001090398,0.0001124943,0.9936493,0.002901016,0.00105571],"genre_scores_gemma":[0.01301073,0.0002449962,0.01802704,0.001104201,0.0002825812,0.002582012,0.9413919,0.01198085,0.01137572],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8798087,"threshold_uncertainty_score":0.1714383,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02352179973318713,"score_gpt":0.2413057400578173,"score_spread":0.2177839403246302,"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."}}