{"id":"W4395677233","doi":"10.21203/rs.3.rs-4268783/v1","title":"Raising awareness may increase the likelihood of hematopoietic stem cell donation: analysis of a nationwide survey using Artificial Intelligence","year":2024,"lang":"en","type":"preprint","venue":"Research Square","topic":"Hematopoietic Stem Cell Transplantation","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Hospital Foundation","funders":"","keywords":"Raising (metalworking); Donation; Haematopoiesis; Stem cell; Computer science; Biology; Engineering; Genetics; Economics; Economic growth","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":[],"consensus_categories":[],"category_scores_codex":[0.002247353,0.0001464958,0.0002191976,0.0009587886,0.0003586915,0.0007933162,0.0003405641,0.000705287,0.001739561],"category_scores_gemma":[0.006480439,0.0002028819,0.0006484919,0.001343111,0.0003903612,0.0005784403,0.0006367132,0.0007167937,0.0003205479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004427364,"about_ca_system_score_gemma":0.0004345572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005932414,"about_ca_topic_score_gemma":0.004807035,"domain_scores_codex":[0.9987766,0.0006159985,0.0001338594,0.0001227331,0.0001746241,0.0001761207],"domain_scores_gemma":[0.9939994,0.002422791,0.002406239,0.0002884379,0.0004056199,0.000477609],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002368234,0.00008852741,0.9972799,0.00002186095,0.00002299514,0.00003026049,0.0006264415,0.000031303,0.00005461427,0.00001761534,0.0001342948,0.001668439],"study_design_scores_gemma":[0.000001388501,0.00005589623,0.9984416,0.00001029419,0.00001085587,0.00002978276,0.001086121,0.0001741761,0.00001733516,0.00001122243,0.000158955,0.000002391986],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989915,0.00004486381,0.00007323149,0.0001223854,0.000003748832,0.00001639219,0.0001796455,0.000001780034,0.0005665559],"genre_scores_gemma":[0.9993958,0.00006891467,0.00008825222,0.00006380997,0.000006471845,0.00002958459,0.0002048715,9.77977e-7,0.0001412857],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005932414,"threshold_uncertainty_score":0.01188529,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1832890744464662,"score_gpt":0.4365801691238616,"score_spread":0.2532910946773954,"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."}}