{"id":"W2388267448","doi":"","title":"Impact of Aqueous Extract of Red Beet Hemorrhagic Anemia in Mice","year":2015,"lang":"en","type":"article","venue":"Shipin yanjiu yu kaifa","topic":"Lipid metabolism and disorders","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Science North","funders":"","keywords":"Hemoglobin; Red blood cell; Anemia; Distilled water; Chemistry; Medicine; Aqueous extract; Animal science; Pharmacology; Internal medicine; Traditional medicine; Biology; Chromatography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000497091,0.000210564,0.0006674737,0.0002756028,0.00001145262,0.000005948293,0.0001756399,0.0001730908,0.0002492609],"category_scores_gemma":[0.0006775041,0.0001721415,0.0002036344,0.0004926372,0.0001193885,0.0001050456,0.00004665518,0.0002377221,0.00002668571],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008243456,"about_ca_system_score_gemma":0.0005642938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002026903,"about_ca_topic_score_gemma":0.0001134458,"domain_scores_codex":[0.9983413,0.0000873262,0.000561155,0.0002708701,0.0003830723,0.0003562292],"domain_scores_gemma":[0.998784,0.00008307151,0.0002184528,0.0004609309,0.0001745382,0.000279002],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004846381,0.002646982,0.6760339,0.001057243,0.000196764,0.0002132044,0.004945924,0.0002729198,0.241552,0.0003437072,0.01956508,0.04832595],"study_design_scores_gemma":[0.01551366,0.001814047,0.9463711,0.0003919411,0.0003249974,0.0002010911,0.001885923,0.0005358371,0.02778544,0.001816103,0.00276123,0.0005986037],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9784919,0.002543192,0.00001795301,0.0002387281,0.0002621493,0.0003481045,0.00002855651,0.00003369787,0.0180357],"genre_scores_gemma":[0.9982078,0.00008500864,0.0008531726,0.0001043665,0.0001590021,0.000006265498,0.00004677702,0.00003193155,0.0005056977],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2703373,"threshold_uncertainty_score":0.7019727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03064122995364724,"score_gpt":0.3158974268236445,"score_spread":0.2852561968699972,"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."}}