{"id":"W4402471159","doi":"10.1182/bloodadvances.2024012982","title":"Point-of-care CAR T manufacturing solutions: can 1 model fit all?","year":2024,"lang":"en","type":"article","venue":"Blood Advances","topic":"CAR-T cell therapy research","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ottawa Hospital","funders":"","keywords":"Point (geometry); Computer science; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001102138,0.0001390195,0.0002420408,0.0001480543,0.00005411695,0.00002417905,0.0001165268,0.00005709824,0.0004435884],"category_scores_gemma":[0.00002985213,0.0001109928,0.0001401624,0.0001200154,0.0000809088,0.0001345374,0.00006356501,0.000236563,0.00002043131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006726445,"about_ca_system_score_gemma":0.0001577493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005457287,"about_ca_topic_score_gemma":0.0001059877,"domain_scores_codex":[0.9988053,0.0000194049,0.0001989677,0.0002891086,0.000350763,0.0003364126],"domain_scores_gemma":[0.9994181,0.0000805144,0.00002528074,0.0002982719,0.00006434447,0.0001135131],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006351784,0.0005926078,0.001660842,0.008620049,0.001699252,0.0009152137,0.01077464,0.01435672,0.4534036,0.003686697,0.002450392,0.5012048],"study_design_scores_gemma":[0.002153285,0.0007997872,0.0003463697,0.001312864,0.000557914,0.0002144372,0.002626091,0.01127997,0.757784,0.003505742,0.2189498,0.0004697598],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8292931,0.1432203,0.0005586706,0.003133065,0.0004856098,0.001016589,0.000156894,0.0003971838,0.02173854],"genre_scores_gemma":[0.9844108,0.00339741,0.002312167,0.0001491234,0.0002424581,0.00005164406,0.00003096436,0.00004387602,0.009361596],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.500735,"threshold_uncertainty_score":0.4856982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04513051343112905,"score_gpt":0.3392272802269209,"score_spread":0.2940967667957919,"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."}}