{"id":"W7019622783","doi":"","title":"Identifying determinants and estimating the risk of inadequate and excess gestational weight gain using a multinomial logistic regression model","year":2014,"lang":"en","type":"other","venue":"Dove Medical Press (Taylor and Francis Group)","topic":"Gestational Diabetes Research and Management","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Multinomial logistic regression; Logistic regression; Multinomial distribution; Binomial regression; Weight gain; Regression analysis; Singleton; Regression","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":[0.01987291,0.001494188,0.001951027,0.002731931,0.000667602,0.001960222,0.002426481,0.001523004,0.00230334],"category_scores_gemma":[0.04387797,0.001056672,0.00295236,0.001803075,0.0005408154,0.001173208,0.002297546,0.002842611,0.0005208523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008738296,"about_ca_system_score_gemma":0.002230055,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02806979,"about_ca_topic_score_gemma":0.01649091,"domain_scores_codex":[0.9907758,0.006964329,0.0003964989,0.0009480198,0.0004685943,0.0004468229],"domain_scores_gemma":[0.9567261,0.0383007,0.002348512,0.0009810477,0.001017942,0.0006257424],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000816697,0.0003841136,0.8709915,0.0001319848,0.001610719,0.0005096109,0.0004252111,0.08905524,0.0005594339,0.002318213,0.001056239,0.03214099],"study_design_scores_gemma":[0.00007401499,0.0002243884,0.05315318,0.00008759222,0.0002944802,0.0002026185,0.0002923408,0.9429828,0.000141657,0.002083402,0.0004233032,0.00004018855],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8214219,0.0008775202,0.1739366,0.001336809,0.0001019676,0.0003167163,0.0008315381,0.0002902992,0.0008867666],"genre_scores_gemma":[0.9362773,0.0004116536,0.06068797,0.0001056415,0.00006342639,0.0003447791,0.0008786426,0.00004293634,0.001187798],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02806979,"threshold_uncertainty_score":0.1050992,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05147584832972283,"score_gpt":0.342469622828628,"score_spread":0.2909937744989051,"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."}}