{"id":"W3118862122","doi":"10.1039/d0re00321b","title":"A data-driven approach to generate pseudo-reaction sequences for the thermal conversion of Athabasca bitumen","year":2021,"lang":"en","type":"article","venue":"Reaction Chemistry & Engineering","topic":"Petroleum Processing and Analysis","field":"Chemistry","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Hospital Edmonton","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates; University of Alberta","keywords":"Asphalt; Oil sands; Multivariate statistics; Thermal; Mineralogy; Materials science; Computer science; Chemistry; Thermodynamics; Physics; Composite material","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001367832,0.0001538068,0.0001914861,0.00002215712,0.0001001831,0.00004527666,0.0002758317,0.00009923748,0.00002935949],"category_scores_gemma":[0.00008476193,0.000132971,0.0001005737,0.0002033378,0.00001734028,0.0001630623,0.00007721326,0.0001680046,0.000002312735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008987531,"about_ca_system_score_gemma":0.00007784145,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004695619,"about_ca_topic_score_gemma":6.268332e-7,"domain_scores_codex":[0.9990254,0.000004170651,0.0002221403,0.0003618007,0.0001963645,0.0001900964],"domain_scores_gemma":[0.9991239,0.00007567583,0.0001176249,0.000498469,0.0001141127,0.00007020953],"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":[0.00001191999,0.00003808611,0.0000592646,0.00043565,0.0001321617,9.533127e-7,0.00004549582,0.019116,0.9790483,0.00000287298,0.00005877779,0.001050489],"study_design_scores_gemma":[0.0001582266,0.000001826646,0.00002609786,0.00006154056,0.0001127393,0.00002405393,0.0002422455,0.2350631,0.7532454,3.186355e-7,0.01094454,0.0001199222],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.985797,0.000279149,0.01022322,0.0001302544,0.0000790759,0.00001826249,0.0001093322,0.0001117842,0.003251924],"genre_scores_gemma":[0.9944662,0.00006336196,0.002438851,0.00001212457,0.0003966752,0.00003634517,0.0005969143,0.00002455414,0.001964955],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2258029,"threshold_uncertainty_score":0.5422399,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0249257805703874,"score_gpt":0.243574255906901,"score_spread":0.2186484753365135,"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."}}