{"id":"W3157171838","doi":"10.52716/jprs.v9i1.269","title":"التحليل الكمي للمجاميع العضوية باستخدام تقنية الاشعة تحت الحمراء","year":2019,"lang":"ar","type":"article","venue":"Journal of Petroleum Research and Studies","topic":"Chemistry and Chemical Engineering","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Agriculture","funders":"","keywords":"Xylene; Chemistry; m-Xylene; Nuclear chemistry; Medicinal chemistry; Organic chemistry; Toluene","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001445716,0.0007680126,0.0004178,0.001049393,0.002296888,0.004211883,0.0007965823,0.001701684,0.351509],"category_scores_gemma":[0.002772499,0.0007998775,0.0004718969,0.001128089,0.001847377,0.002550268,0.002377828,0.002656294,0.2744503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001732156,"about_ca_system_score_gemma":0.002069509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001723168,"about_ca_topic_score_gemma":0.002554407,"domain_scores_codex":[0.9986967,0.0001608512,0.00007619843,0.0001648954,0.0006997117,0.000201654],"domain_scores_gemma":[0.9979103,0.0005229295,0.0001492549,0.0003086716,0.000837599,0.0002711905],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007223561,0.0003602285,0.003868395,0.00148757,0.00002906562,0.00130539,0.003935625,0.000783545,0.1763949,0.05101081,0.3016841,0.4584179],"study_design_scores_gemma":[0.00003157551,0.0001302425,0.00470355,0.0002138787,0.00001154559,0.0005938802,0.002333583,0.0002963487,0.05883908,0.004107134,0.9286795,0.00005964699],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02572125,0.001766908,0.02027808,0.006799574,0.004125743,0.0003893703,0.001589465,0.002284077,0.9370456],"genre_scores_gemma":[0.06461039,0.002863211,0.02337017,0.002459393,0.0005081136,0.0005424858,0.001789431,0.002525423,0.9013314],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.351509,"threshold_uncertainty_score":0.9249936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05655120746955129,"score_gpt":0.3575391064452651,"score_spread":0.3009878989757138,"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."}}