{"id":"W6942386051","doi":"10.1371/journal.pone.0304293.s007","title":"Data extraction table.","year":2025,"lang":"en","type":"article","venue":"Figshare","topic":"Inflammatory Bowel Disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Iron deficiency; CINAHL; Population; Disease; Inclusion (mineral); Data extraction; Iron status; Inflammatory bowel disease","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":[0.01571933,0.003503816,0.01344543,0.02710265,0.001916008,0.005355937,0.004120551,0.002811024,0.4905879],"category_scores_gemma":[0.08490945,0.002916428,0.005711467,0.02850423,0.001315488,0.004097125,0.003444111,0.003673353,0.0763559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006470148,"about_ca_system_score_gemma":0.02636966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009915121,"about_ca_topic_score_gemma":0.007729779,"domain_scores_codex":[0.9857088,0.002986261,0.006885787,0.001696676,0.002122855,0.0005994734],"domain_scores_gemma":[0.9378904,0.03086597,0.005483465,0.004811528,0.01960167,0.001346889],"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":[0.001642136,0.0001159329,0.0005630258,0.3135311,0.0005438325,0.0003663966,0.0006370014,0.0004914373,0.0003184295,0.005058105,0.6049769,0.07175571],"study_design_scores_gemma":[0.005147246,0.0002922768,0.003253735,0.124865,0.001066041,0.0002187422,0.001343995,0.0005649977,0.000709131,0.01222828,0.8500923,0.0002183591],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0009131441,0.003818027,0.003611422,0.001668788,0.001472159,0.1012627,0.868899,0.0008779451,0.01747677],"genre_scores_gemma":[0.005068681,0.009984289,0.02877265,0.002515008,0.0004532098,0.7525963,0.1755527,0.0009987412,0.02405856],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.5094122,"threshold_uncertainty_score":0.7266146,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03180366791898125,"score_gpt":0.3081578797971992,"score_spread":0.276354211878218,"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."}}