{"id":"W4379929625","doi":"10.21203/rs.3.rs-2958834/v1","title":"Prediction of malnutrition in newbornInfants using machine learning techniques","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Child Nutrition and Water Access","field":"Nursing","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bow Valley College","funders":"","keywords":"Malnutrition; Logistic regression; Underweight; Machine learning; Artificial intelligence; Naive Bayes classifier; Support vector machine; Medicine; Computer science; Pediatrics; Obesity; Internal medicine; Overweight","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008656902,0.000731699,0.0005447296,0.001776586,0.0001599796,0.0006811211,0.000351786,0.0005542028,0.001280089],"category_scores_gemma":[0.003193117,0.0001395726,0.0005499751,0.0007597592,0.0001179933,0.0004681661,0.0003153278,0.0004698157,0.0005446012],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000392397,"about_ca_system_score_gemma":0.0003609727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004111351,"about_ca_topic_score_gemma":0.002207892,"domain_scores_codex":[0.9997323,0.00009060296,0.0000276199,0.00005608609,0.00005678988,0.0000364701],"domain_scores_gemma":[0.9987214,0.0008239922,0.0001678867,0.00004025896,0.0001930479,0.00005349809],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006999014,0.0007472124,0.4207428,0.0002784943,0.0002666159,0.0003468563,0.00006810954,0.2556648,0.004974786,0.0006828951,0.004936901,0.3105906],"study_design_scores_gemma":[0.000009393698,0.0001888973,0.04329098,0.00004681854,0.00002942691,0.00007994159,0.00005379769,0.9530175,0.002044289,0.0006889856,0.0005356964,0.0000141332],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8848801,0.002252179,0.1060311,0.0006058706,0.0001651878,0.000122454,0.002152901,0.00106088,0.002729485],"genre_scores_gemma":[0.9662674,0.0006396745,0.02958923,0.00004997434,0.00005199359,0.00006362818,0.002000402,0.00001958937,0.001318063],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004111351,"threshold_uncertainty_score":0.008174837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1620009983742213,"score_gpt":0.4261651936869099,"score_spread":0.2641641953126886,"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."}}