{"id":"W4407204568","doi":"10.1016/j.beha.2025.101596","title":"Analyte heterogeneity analysis as a possible potency parameter for MSC","year":2024,"lang":"en","type":"review","venue":"Best Practice & Research Clinical Haematology","topic":"Additive Manufacturing and 3D Printing Technologies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Biotechnology Research Institute","funders":"National Institute of Neurological Disorders and Stroke; National Institutes of Health; Cleveland Clinic; U.S. Department of Defense","keywords":"Potency; Analyte; Medicine; Computational biology; Chemistry; Pharmacology; Biology; Chromatography; Biochemistry; In vitro","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":["metaresearch","metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.007321957,0.0007609064,0.004393049,0.001994326,0.000261571,0.0003649388,0.00157029,0.001961519,0.0001042817],"category_scores_gemma":[0.04612941,0.000597791,0.00242673,0.003022548,0.0008193476,0.0002573024,0.001086863,0.00533398,0.002982297],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001947713,"about_ca_system_score_gemma":0.0004994968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001054524,"about_ca_topic_score_gemma":0.00008197847,"domain_scores_codex":[0.9921309,0.002010074,0.002187704,0.001561863,0.000672801,0.001436627],"domain_scores_gemma":[0.9679934,0.02882515,0.0003941467,0.001839017,0.0006282031,0.0003201222],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003921997,0.0003386964,0.00001170735,0.01420876,0.01153952,0.00125566,0.00001587294,0.00002006682,6.11616e-8,0.001958149,0.00959311,0.9610192],"study_design_scores_gemma":[0.0001370587,0.0005199319,0.00000159471,0.001957332,0.01275742,0.0005489849,0.00007033684,0.0009447535,0.00001348945,0.002779609,0.9797082,0.0005613141],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000382101,0.9906141,0.002435873,0.0005420272,0.0007406936,0.001506711,0.000196312,0.001096462,0.002485724],"genre_scores_gemma":[0.0005402158,0.9897414,0.007163372,0.00003333147,0.0002955799,0.001005845,0.0001705457,0.0001834983,0.0008661588],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9701151,"threshold_uncertainty_score":0.9996473,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.31467406031385,"score_gpt":0.5639640742838706,"score_spread":0.2492900139700207,"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."}}