{"id":"W7052151606","doi":"","title":"Rapid synthesis: Features and impacts of individualized funding models for children and youth with support needs and their families.","year":2023,"lang":"en","type":"other","venue":"","topic":"Plasma Diagnostics and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Needs assessment; Evidence-based practice; Key (lock); Data collection; MEDLINE; Matching (statistics); Government (linguistics)","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":[],"consensus_categories":[],"category_scores_codex":[0.1369736,0.001697599,0.003276134,0.009700759,0.001433105,0.01013628,0.003394561,0.004571171,0.07474748],"category_scores_gemma":[0.3712379,0.001140792,0.007181949,0.01034973,0.001418571,0.005449541,0.007201799,0.004090328,0.005312903],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0125989,"about_ca_system_score_gemma":0.03547812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01920682,"about_ca_topic_score_gemma":0.04138151,"domain_scores_codex":[0.886371,0.07951172,0.01504792,0.002229704,0.01475924,0.00208046],"domain_scores_gemma":[0.6599743,0.2636078,0.01795313,0.01630581,0.03927913,0.002879845],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.003067037,0.0001431518,0.001430045,0.3977788,0.005495884,0.0002444231,0.002843854,0.001412721,0.000492124,0.02381552,0.2466852,0.3165913],"study_design_scores_gemma":[0.004400832,0.0006064223,0.006148605,0.4055502,0.01213116,0.0001707845,0.004699571,0.0009977663,0.001124642,0.02843472,0.5355212,0.0002141126],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.009907723,0.2924637,0.02932337,0.1765238,0.02121693,0.0805837,0.2182753,0.002008565,0.169697],"genre_scores_gemma":[0.1472944,0.2391712,0.2700345,0.04877749,0.004887243,0.2142208,0.04648257,0.0009889388,0.02814288],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.1369736,"threshold_uncertainty_score":0.7243943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01535887678667474,"score_gpt":0.2090478281377305,"score_spread":0.1936889513510557,"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."}}