{"id":"W2073749845","doi":"10.2134/jeq2006.0008","title":"Preparation and FT–IR Characterization of Metal Phytate Compounds","year":2006,"lang":"en","type":"article","venue":"Journal of Environmental Quality","topic":"Phytase and its Applications","field":"Agricultural and Biological Sciences","cited_by":145,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"University of Georgia Research Foundation","keywords":"Characterization (materials science); Metal; Chemistry; Environmental chemistry; Nuclear chemistry; Materials science; Organic chemistry; Nanotechnology","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":[0.000195095,0.00004721041,0.0001136178,0.0000056485,0.00004877931,0.000009859606,0.00004755711,0.00002323798,0.00006801187],"category_scores_gemma":[0.000002526172,0.00002008154,0.00004630839,0.00003962002,0.00004993957,0.0001774487,0.00001535797,0.00003754524,0.000002097694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001426045,"about_ca_system_score_gemma":0.000001511718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002475637,"about_ca_topic_score_gemma":0.00001137836,"domain_scores_codex":[0.9993973,0.00005085425,0.0003090821,0.00006167017,0.0001302498,0.00005088536],"domain_scores_gemma":[0.9995602,0.00003021425,0.000354408,0.00002179218,0.000007881561,0.00002546133],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0000236047,0.0001587579,0.01036757,0.000002027342,0.000006212752,1.691172e-7,0.00002183014,0.00000106748,0.9858176,0.0001362035,0.00002409441,0.003440917],"study_design_scores_gemma":[0.00009051745,0.0001187498,0.9125164,0.000003435346,0.00001116729,0.000006330671,0.00003654643,0.000007671977,0.08294252,0.0005017735,0.003724162,0.00004075818],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994091,0.00006612237,0.00001837506,0.000171442,0.00001961622,0.00005280751,0.00009636589,0.000002179246,0.0001640019],"genre_scores_gemma":[0.9996326,0.00006590851,0.00004453698,0.00003124694,0.0001035269,9.642746e-7,0.00007595121,3.184995e-7,0.00004493846],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.902875,"threshold_uncertainty_score":0.08189013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01848673599639883,"score_gpt":0.2555395932446566,"score_spread":0.2370528572482578,"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."}}