{"id":"W3084105976","doi":"10.1016/j.watres.2020.116415","title":"Electrokinetic study of calcium carbonate and magnesium hydroxide particles in lime softening","year":2020,"lang":"en","type":"article","venue":"Water Research","topic":"Enhanced Oil Recovery Techniques","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":false,"ca_institutions":"Suncor Energy (Canada); Stantec (Canada); University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates; Suncor Energy Incorporated; Canada First Research Excellence Fund; University of Calgary","keywords":"Magnesium; Electrokinetic phenomena; Calcium carbonate; Lime; Calcium hydroxide; Chemistry; Calcium; Calcite; Softening; Carbonate; Chemical engineering; Inorganic chemistry; Mineralogy; Metallurgy; Materials science; Organic chemistry","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":[0.0004054168,0.00009241604,0.0001681192,0.0001576661,0.00002091746,0.00002465578,0.0001443788,0.00004347815,0.00001334659],"category_scores_gemma":[0.00004216882,0.00007668443,0.00001358336,0.0002631274,0.00004175418,0.00008051936,0.0001202356,0.0003330102,0.000009342506],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003660691,"about_ca_system_score_gemma":0.000007044977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002264979,"about_ca_topic_score_gemma":0.0000845015,"domain_scores_codex":[0.998787,0.0001042739,0.0002055837,0.0001897032,0.0002761045,0.0004372637],"domain_scores_gemma":[0.999702,0.00003420779,0.00000646415,0.0001373767,0.0000394901,0.00008042328],"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":[0.00003614552,0.00004131767,0.01359624,0.0001339541,0.000009412635,0.00003955716,0.003192201,0.001155908,0.980217,0.000009074334,0.00002632442,0.001542914],"study_design_scores_gemma":[0.0003406904,0.0005315399,0.005715589,0.00001590064,0.000003581307,0.000002043447,0.0002772133,0.0197273,0.9728724,0.0003519676,0.0000611574,0.0001005999],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984574,0.0001930648,0.00006408913,0.000146599,0.00001001474,0.0002922695,7.889628e-7,0.0001324146,0.0007033145],"genre_scores_gemma":[0.9996061,0.00002142122,0.0002129682,0.000008063615,0.00002049586,0.00006759983,8.464013e-7,0.00003064511,0.00003183391],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01857139,"threshold_uncertainty_score":0.31271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05691506339635201,"score_gpt":0.3127421878505148,"score_spread":0.2558271244541628,"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."}}