{"id":"W6960788170","doi":"10.1371/journal.pone.0307306.s005","title":"Program source links.","year":2024,"lang":"en","type":"article","venue":"Figshare","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Grey literature; Transitional care; Health care; Scope (computer science); Inclusion (mineral); Best practice; Population; MEDLINE","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.004179101,0.0009149488,0.001354476,0.01287345,0.003644753,0.005316732,0.003555701,0.002097537,0.809925],"category_scores_gemma":[0.02915281,0.0007946157,0.0009889911,0.02023201,0.0006270088,0.003397337,0.004672746,0.002109757,0.3871842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008695057,"about_ca_system_score_gemma":0.03947515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2863623,"about_ca_topic_score_gemma":0.3484004,"domain_scores_codex":[0.9971256,0.0004406523,0.0003115198,0.0003820927,0.001207474,0.0005326507],"domain_scores_gemma":[0.9787376,0.003953495,0.0006303371,0.001145698,0.01293647,0.002596467],"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":[0.00003092405,0.00001259744,0.0001881144,0.001478281,0.000005123809,0.00002473454,0.0001208085,0.00002997036,0.00002662578,0.001171996,0.972136,0.0247749],"study_design_scores_gemma":[0.00001830818,0.000005071624,0.0007220161,0.0009302843,0.000008593022,0.0000185174,0.0001610119,0.00002305717,0.0000396376,0.0004259855,0.9976389,0.000008603379],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0003319819,0.001548927,0.001191857,0.00398843,0.001208345,0.001232744,0.6836678,0.002176971,0.3046528],"genre_scores_gemma":[0.006409668,0.006696625,0.007406895,0.004215137,0.0006070314,0.005274076,0.486573,0.003626744,0.4791909],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.2863623,"threshold_uncertainty_score":0.5693911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08122380339518305,"score_gpt":0.2390593663793497,"score_spread":0.1578355629841666,"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."}}