{"id":"W4380082095","doi":"10.3390/en16124610","title":"Current Status and Future Trends of In Situ Catalytic Upgrading of Extra Heavy Oil","year":2023,"lang":"en","type":"article","venue":"Energies","topic":"Petroleum Processing and Analysis","field":"Chemistry","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"China University of Geosciences; China University of Petroleum, Beijing; National Natural Science Foundation of China","keywords":"Catalysis; Environmental science; In situ; Automatic summarization; Waste management; Petroleum engineering; Nanotechnology; Process engineering; Materials science; Chemistry; Engineering; Computer science","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":[0.00006039088,0.00008291225,0.0002067121,0.0002175023,0.00002261947,0.00001053374,0.00006943036,0.00003959251,0.0000216263],"category_scores_gemma":[0.00001307921,0.00007479524,0.00005057018,0.0004797463,0.0000508761,0.00005041383,0.0000335231,0.0000807751,6.320933e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001683515,"about_ca_system_score_gemma":0.00002710699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008938926,"about_ca_topic_score_gemma":0.00007039039,"domain_scores_codex":[0.9993879,0.000006351545,0.0001852379,0.0001372163,0.0001220597,0.0001612047],"domain_scores_gemma":[0.9997176,0.0000313881,0.00007620079,0.0001251048,0.00001621142,0.00003349297],"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":[0.00002249051,0.00006402903,0.01850125,0.0009829544,0.00005304421,0.000006748689,0.002027203,0.001132594,0.2514756,0.0002043677,0.0002288183,0.7253009],"study_design_scores_gemma":[0.001611295,0.00003417031,0.02621361,0.001008547,0.000205516,0.000004630152,0.009333289,0.00305928,0.9162745,0.0003291432,0.04135068,0.0005752931],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.987181,0.007695329,3.337543e-7,0.00007820928,0.00003429252,4.175921e-7,0.00001463041,0.00003393033,0.004961825],"genre_scores_gemma":[0.9938954,0.002964566,0.00002245789,0.000001375562,0.00007989679,0.000002492723,0.00004241103,0.000007649448,0.002983715],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7247256,"threshold_uncertainty_score":0.3050061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01257267936428428,"score_gpt":0.261352416826685,"score_spread":0.2487797374624008,"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."}}