{"id":"W4387114978","doi":"10.1002/path.6199","title":"Hourglass, a rapid analysis framework for heterogeneous bioimaging data, identifies sex disparity in <scp>IL</scp>‐6/<scp>STAT3</scp>‐associated immune phenotypes in pancreatic cancer","year":2023,"lang":"en","type":"article","venue":"The Journal of Pathology","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital; Translational Research in Oncology; Ontario Institute for Cancer Research; University Health Network; University of Toronto; Princess Margaret Cancer Centre","funders":"Canadian Institutes of Health Research; Princess Margaret Hospital Foundation; Deutsche Forschungsgemeinschaft; Canadian Cancer Society; Alexander von Humboldt-Stiftung; European Molecular Biology Organization","keywords":"Hourglass; Pancreatic cancer; Computer science; Digital pathology; Computational biology; Data science; Medicine; Bioinformatics; Biology; Artificial intelligence; Cancer; Internal medicine; Geography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00322318,0.001573798,0.001126084,0.004651377,0.0009080492,0.004002551,0.001541713,0.0009135054,0.008213581],"category_scores_gemma":[0.007595127,0.0009090053,0.002468114,0.002127303,0.0007359501,0.001984117,0.003901151,0.001368443,0.00295398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009912963,"about_ca_system_score_gemma":0.0024995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006717674,"about_ca_topic_score_gemma":0.02185157,"domain_scores_codex":[0.9990066,0.0001743586,0.00007568453,0.0003508393,0.0003004071,0.00009207387],"domain_scores_gemma":[0.9976823,0.001229094,0.0002617174,0.0003955498,0.0002612548,0.0001699092],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00155093,0.0003917449,0.03573668,0.003009193,0.002373846,0.001746532,0.002192255,0.05893949,0.07219746,0.03855694,0.1985824,0.5847226],"study_design_scores_gemma":[0.0002513977,0.0003504135,0.0278103,0.0003883136,0.0004457862,0.001333764,0.001189005,0.5797044,0.05079823,0.130361,0.2069088,0.0004585963],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0152563,0.001400008,0.8449568,0.0008837525,0.0001957038,0.0003047464,0.03497211,0.1003449,0.001685749],"genre_scores_gemma":[0.1047918,0.001712398,0.819796,0.0006504341,0.0002131867,0.001102249,0.05811818,0.0101397,0.003476069],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008213581,"threshold_uncertainty_score":0.02747715,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02786218957276002,"score_gpt":0.2914182104532901,"score_spread":0.26355602088053,"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."}}