{"id":"W7111367061","doi":"10.1371/journal.pone.0329794.s005","title":"Data extraction – study characteristics.","year":2025,"lang":"","type":"article","venue":"Figshare","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cluster analysis; Cluster (spacecraft); Population; Latent class model; Multimorbidity; Set (abstract data type); Medoid","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":[],"category_scores_codex":[0.04773343,0.003535846,0.01396554,0.03737994,0.001278029,0.005594621,0.005017609,0.004385717,0.1023873],"category_scores_gemma":[0.2271813,0.002383248,0.01150465,0.03222891,0.001647796,0.005399172,0.00417433,0.002909031,0.01934179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007293312,"about_ca_system_score_gemma":0.02285726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006743304,"about_ca_topic_score_gemma":0.006194138,"domain_scores_codex":[0.8854861,0.02350412,0.07096129,0.007928695,0.01004718,0.002072667],"domain_scores_gemma":[0.8351002,0.08545255,0.0334997,0.01457754,0.03015478,0.00121523],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001723302,0.00009321507,0.004346317,0.8103852,0.003655812,0.0003271157,0.00137696,0.0005843707,0.0004401449,0.003121064,0.1026071,0.07133953],"study_design_scores_gemma":[0.006342964,0.0007636835,0.02927259,0.5063998,0.009313232,0.0004772469,0.001652735,0.001545544,0.001504354,0.0125292,0.4298145,0.00038411],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.005454135,0.02171605,0.0107472,0.002433772,0.00147975,0.2672539,0.6765833,0.001351236,0.0129806],"genre_scores_gemma":[0.01514143,0.007667197,0.02598286,0.0019562,0.0003166374,0.881889,0.06195046,0.0005898367,0.004506448],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8976127,"threshold_uncertainty_score":0.3425198,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1735763384276686,"score_gpt":0.4248427373501769,"score_spread":0.2512663989225082,"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."}}