{"id":"W4411182103","doi":"10.2139/ssrn.5287635","title":"Assessing Process Feasibility of Salinity Gradient Systems Through Maximum Extractable and Net Energy Outputs","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Process Optimization and Integration","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Salinity; Process (computing); Environmental science; Energy (signal processing); Net (polyhedron); Computer science; Mathematics; Statistics; Geology; Oceanography","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009792338,0.000312078,0.0004931727,0.0001542785,0.0001219148,0.0002784305,0.0002797228,0.0003165448,0.000006438397],"category_scores_gemma":[0.00008658144,0.0002938719,0.00009995276,0.0001880234,0.00004315209,0.0005638169,0.00007231254,0.002200853,3.232657e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009738804,"about_ca_system_score_gemma":0.001995001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001961456,"about_ca_topic_score_gemma":0.000253164,"domain_scores_codex":[0.9976615,0.0000984065,0.0006962967,0.0003039545,0.0002779564,0.0009619028],"domain_scores_gemma":[0.9989495,0.00003975617,0.000343824,0.0002420411,0.0003580967,0.00006684234],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00008280368,0.0002883156,0.002481108,0.003619373,0.0008302055,0.000003187323,0.001236759,0.8642076,0.0003041457,0.1096831,0.000250796,0.01701264],"study_design_scores_gemma":[0.001269578,0.0002016398,0.0003786068,0.001955543,0.000323414,0.0002559492,0.004808865,0.4801665,0.002265668,0.5063582,0.0009655302,0.001050536],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06378711,0.03125845,0.8975933,0.0000786938,0.001273088,0.0002811353,0.00002924109,0.0001682826,0.005530702],"genre_scores_gemma":[0.984697,0.01430142,0.0004518548,0.00001584359,0.0001391593,0.0000214497,0.00004774944,0.00002847707,0.0002970755],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9209099,"threshold_uncertainty_score":0.9999514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02384751514109739,"score_gpt":0.2927046656243842,"score_spread":0.2688571504832868,"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."}}