{"id":"W4318159619","doi":"10.34067/kid.0000000000000021","title":"A Midterm Analysis of Kidney360","year":2023,"lang":"en","type":"editorial","venue":"Kidney360","topic":"Organ Donation and Transplantation","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Political science; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002928209,0.0002752359,0.0009882632,0.001428321,0.00003924137,0.00002051138,0.0001645846,0.0007277586,0.001206573],"category_scores_gemma":[0.001742745,0.0002593811,0.0005459625,0.001962156,0.0000716408,0.00004960235,0.00002489536,0.0005153417,0.0001962816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009494636,"about_ca_system_score_gemma":0.0007196407,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001199357,"about_ca_topic_score_gemma":0.00005813346,"domain_scores_codex":[0.9975117,0.00004644229,0.0005882173,0.0004373394,0.001166114,0.0002501646],"domain_scores_gemma":[0.9978781,0.0005608743,0.0002970543,0.0004937588,0.0004498059,0.0003204595],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00012885,0.00009673895,0.0006766348,0.000663561,0.003553922,0.00006410852,0.0002953958,0.000003178092,0.0004013373,0.00003520603,0.9937655,0.0003156143],"study_design_scores_gemma":[0.001657876,0.0001317356,0.005904023,0.0003435053,0.01477289,0.000001232981,0.00003052072,0.000194158,0.0008759278,0.00002667719,0.9757993,0.0002621791],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.0009832599,0.00009160114,0.0001381523,0.0009153015,0.988323,0.0003363687,0.003404096,0.0002794941,0.005528763],"genre_scores_gemma":[0.01043957,0.001336975,0.0003561816,0.0004574375,0.8999463,0.00005842589,0.04835291,0.0002258947,0.03882624],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.0883766,"threshold_uncertainty_score":0.9999858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01146017970140139,"score_gpt":0.3132399091026057,"score_spread":0.3017797294012043,"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."}}