{"id":"W1996991143","doi":"10.1021/ef050097g","title":"Derivation of Molecular Representations of Middle Distillates","year":2005,"lang":"en","type":"article","venue":"Energy & Fuels","topic":"Process Optimization and Integration","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Hydrocarbon mixtures; Chemistry; Distillation; Representation (politics); Hydrocarbon; Combining rules; Homologous series; Molecule; Mixing (physics); Biological system; Consistency (knowledge bases); Molecular descriptor; Thermodynamics; Series (stratigraphy); Mass spectrometry; Statistical physics; Quantitative structure–activity relationship; Organic chemistry; Mathematics; Chromatography; Physics","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":[0.0005854741,0.0006653839,0.0005133261,0.0009961245,0.0003552802,0.0008741007,0.001031537,0.0005436549,0.002341554],"category_scores_gemma":[0.001885806,0.0005482971,0.0008763424,0.0004857771,0.0003795188,0.001053841,0.0006705259,0.001034085,0.0009322863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005654009,"about_ca_system_score_gemma":0.001061585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001354248,"about_ca_topic_score_gemma":0.001107694,"domain_scores_codex":[0.9997051,0.00002995408,0.00002172782,0.00004922586,0.0001657927,0.0000282406],"domain_scores_gemma":[0.9996879,0.0001034448,0.00004873827,0.00005601165,0.00008866207,0.0000152161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00009563053,0.00009478658,0.001550762,0.0002896743,0.00004063964,0.0004455915,0.0001326028,0.6732558,0.09054023,0.1425634,0.0008492919,0.09014159],"study_design_scores_gemma":[0.00001051846,0.00005819501,0.0003038814,0.00002196235,0.00001513802,0.00005740146,0.00002090079,0.9558598,0.0289658,0.009681657,0.004986628,0.00001807602],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05114136,0.0002267322,0.9417774,0.00005008562,0.00004087503,0.0001301618,0.0004020166,0.0004613019,0.005770084],"genre_scores_gemma":[0.4289875,0.0006093587,0.5654531,0.00005166086,0.00002719777,0.000385697,0.0008924728,0.0003231542,0.003269895],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002341554,"threshold_uncertainty_score":0.007833302,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009104778908827282,"score_gpt":0.2166627181503276,"score_spread":0.2075579392415003,"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."}}