{"id":"W7162001184","doi":"10.82308/942","title":"Innovations and opportunities for primary health care after hospital discharge: an application of causal inference methods in health services research","year":2017,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Health services; Primary health care; Primary care; Health care; Public health","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":[0.1716902,0.001468841,0.002785739,0.008960208,0.002823542,0.006982775,0.003598793,0.003846956,0.00539631],"category_scores_gemma":[0.3454259,0.00142565,0.005148997,0.009086206,0.00608612,0.008094297,0.006094398,0.004258698,0.0003093238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008453025,"about_ca_system_score_gemma":0.0193841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02297804,"about_ca_topic_score_gemma":0.01798378,"domain_scores_codex":[0.7673166,0.212091,0.004642386,0.008100745,0.006334332,0.001514993],"domain_scores_gemma":[0.312665,0.6688572,0.009734329,0.004835111,0.002823934,0.001084393],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0007178894,0.000897625,0.1450579,0.005953519,0.007551134,0.001048448,0.01068072,0.04886203,0.0002858429,0.5206885,0.00360948,0.254647],"study_design_scores_gemma":[0.0006078926,0.0005897513,0.02475301,0.002638257,0.002154632,0.0002935042,0.005056107,0.2037936,0.0004792807,0.7486745,0.01071902,0.0002403864],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08670194,0.01703257,0.8562261,0.02471451,0.001114389,0.003944798,0.001028398,0.0004096615,0.008827738],"genre_scores_gemma":[0.6035554,0.007337356,0.3797624,0.001975306,0.0005361913,0.004713533,0.0003340755,0.00005510169,0.001730642],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1716902,"threshold_uncertainty_score":0.9079953,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2555043268383185,"score_gpt":0.5826403002615346,"score_spread":0.3271359734232161,"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."}}