{"id":"W2134029260","doi":"10.5539/eer.v3n2p33","title":"Assessment of Investment in Small Hydropower Plants","year":2013,"lang":"en","type":"article","venue":"Energy and Environment Research","topic":"Water resources management and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Hydropower; Investment (military); Flow (mathematics); Work (physics); Value (mathematics); Linear programming; Computer science; Environmental science; Hydrology (agriculture); Water resource management; Environmental economics; Mathematical optimization; Mathematics; Economics; Geology; Engineering; Geotechnical engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001837555,0.00006438589,0.0000765419,0.0001519578,0.00002307196,0.00001784035,0.0000733172,0.0000350369,0.0003192654],"category_scores_gemma":[0.000001151133,0.00005742018,0.000009687614,0.00005498305,0.00005201143,0.00006080153,0.00008428739,0.00007544303,0.00001099837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005123053,"about_ca_system_score_gemma":0.00000176518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002124611,"about_ca_topic_score_gemma":0.00002708795,"domain_scores_codex":[0.9993798,0.00004241399,0.0001181764,0.0001096424,0.0001562898,0.000193691],"domain_scores_gemma":[0.9998069,0.00002008444,0.000008281552,0.0001163999,0.000002569368,0.00004571998],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007849382,0.0002366463,0.04291762,0.0001321997,0.00007515133,0.00001525891,0.0005691954,0.9095692,0.0104807,0.01170333,0.001800558,0.02249233],"study_design_scores_gemma":[0.0009310212,0.0001825922,0.3464488,0.00006455997,0.000004805971,8.234271e-7,0.0002980003,0.5945304,0.0065929,0.005624356,0.04501566,0.0003060583],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9510092,0.0002484039,0.001999947,0.00006229619,0.00002052189,0.0001310308,6.743468e-7,0.00001561735,0.04651227],"genre_scores_gemma":[0.996538,0.001444045,0.0006750976,0.00001475787,0.00001154723,0.00005388395,0.00001315305,0.0000100871,0.001239467],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3150388,"threshold_uncertainty_score":0.3495732,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02121083957706392,"score_gpt":0.2336635741690629,"score_spread":0.212452734591999,"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."}}