{"id":"W1989686363","doi":"10.1021/ef049936+","title":"Quantitative Molecular Representation and Sequential Optimization of Athabasca Asphaltenes","year":2004,"lang":"en","type":"article","venue":"Energy & Fuels","topic":"Petroleum Processing and Analysis","field":"Chemistry","cited_by":245,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Asphaltene; Molecule; Representation (politics); Chemistry; Molecular spectroscopy; Series (stratigraphy); Population; Computational chemistry; Spectroscopy; Biological system; Statistical physics; Organic chemistry; Physics; Quantum mechanics","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":[0.00004282612,0.0000856401,0.0001416604,0.00005637443,0.00004998314,0.00002349833,0.0000626966,0.00005509065,0.00008139925],"category_scores_gemma":[0.00003967268,0.00008581397,0.00006018158,0.0001479635,0.00005748747,0.0001213179,0.00002333363,0.00003666452,7.712585e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001971297,"about_ca_system_score_gemma":0.00003488146,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000422662,"about_ca_topic_score_gemma":0.00001993515,"domain_scores_codex":[0.9993678,0.00001494778,0.0001734481,0.0001979659,0.0001491278,0.00009675969],"domain_scores_gemma":[0.9996111,0.00001818791,0.0001285174,0.0001254332,0.00007831145,0.00003847998],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002383918,0.00003708117,0.0001710288,0.00004205258,0.00008187562,0.00001146145,0.000145232,0.08664711,0.9063864,0.003980886,0.000002539319,0.002470501],"study_design_scores_gemma":[0.0004132498,0.00002096359,0.00002083233,0.00005439905,0.00007013961,0.000005479532,0.0001716616,0.002148754,0.9958162,0.001099947,0.00008381178,0.000094525],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8741124,0.001072218,0.1166888,0.00009685363,0.00002008403,0.000002314332,0.000006284887,0.00003380836,0.007967292],"genre_scores_gemma":[0.9897055,0.0001242584,0.009133502,0.0000264164,0.00002807945,0.000005465733,0.00006311129,0.00001169784,0.0009019744],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1155931,"threshold_uncertainty_score":0.3499392,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01507565701044979,"score_gpt":0.2711371866134131,"score_spread":0.2560615296029634,"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."}}