{"id":"W4412163789","doi":"10.1158/1557-3265.aimachine-b049","title":"Abstract B049: Deep Learning Enables Identification of Cell Types and Clusters (iCTC) in Immune Tumor Ecosystems for Prognostic Assessment in Cancer","year":2025,"lang":"en","type":"article","venue":"Clinical Cancer Research","topic":"Advanced Biosensing Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cancer; Identification (biology); Immune system; Biology; Immunology; Medicine; Computational biology; Genetics; Ecology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006041696,0.000580275,0.0003360262,0.001076281,0.0002705839,0.0006841573,0.0006077857,0.0006682048,0.002801359],"category_scores_gemma":[0.001194122,0.0002204737,0.000383408,0.0007618469,0.0002812184,0.0004589569,0.0007394204,0.000767882,0.001320663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000707256,"about_ca_system_score_gemma":0.0008643451,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005323656,"about_ca_topic_score_gemma":0.005900138,"domain_scores_codex":[0.9997409,0.00004028284,0.0000132195,0.00008328749,0.00007506917,0.00004719086],"domain_scores_gemma":[0.9995748,0.0001106442,0.00006967862,0.00005036935,0.000143635,0.00005088776],"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":[0.0007811793,0.0007293613,0.07277885,0.0002817143,0.0002035424,0.0002385851,0.000165751,0.1075404,0.2685084,0.003883329,0.02391187,0.520977],"study_design_scores_gemma":[0.00002697051,0.0001204128,0.01477132,0.00001840707,0.00003068935,0.00007029653,0.00003751823,0.9328059,0.04571512,0.002492363,0.003887796,0.00002313564],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5261889,0.001009575,0.4474941,0.001228658,0.0001793629,0.0001982086,0.008110074,0.009704364,0.005886912],"genre_scores_gemma":[0.8018842,0.0002634445,0.1878743,0.0002839958,0.00005311434,0.0002213638,0.005259957,0.0001606218,0.003998938],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.005323656,"threshold_uncertainty_score":0.01058531,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06900483981934394,"score_gpt":0.4937628554574379,"score_spread":0.424758015638094,"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."}}