{"id":"W4405471702","doi":"10.70645/3078-3437.1018","title":"Exploring the Major Watershed Basins All Around the World: A Meta-Analysis for Basins Characteristics","year":2024,"lang":"en","type":"article","venue":"AUIQ technical engineering science.","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Watershed; Geography; Geology; Hydrology (agriculture); Computer science; Geotechnical engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007907474,0.001419321,0.004076569,0.009781525,0.0007011517,0.003153423,0.001528175,0.0009973167,0.003506645],"category_scores_gemma":[0.01790424,0.0006536311,0.02418198,0.01551174,0.0004956188,0.001967671,0.002177682,0.001321518,0.0002806596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001188827,"about_ca_system_score_gemma":0.00369015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01926841,"about_ca_topic_score_gemma":0.0243825,"domain_scores_codex":[0.9953799,0.0024157,0.0007135771,0.0008946363,0.000383944,0.0002121536],"domain_scores_gemma":[0.9893492,0.008538797,0.0006290806,0.0007420815,0.0005132884,0.0002275278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.0009153233,0.0001032183,0.2529871,0.05927013,0.5671269,0.0009209398,0.0009890173,0.01443053,0.00167055,0.003319483,0.007824431,0.09044238],"study_design_scores_gemma":[0.0002635841,0.0003881688,0.2046588,0.01527467,0.7129574,0.0008517748,0.002214838,0.01512167,0.001036015,0.008852868,0.03816601,0.0002142025],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.2055945,0.7147157,0.03958113,0.004166089,0.0004881917,0.0006336931,0.03049248,0.0007417619,0.003586547],"genre_scores_gemma":[0.868638,0.0966218,0.02235171,0.0006996005,0.000107966,0.0008013512,0.009867506,0.0002760236,0.0006360829],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01926841,"threshold_uncertainty_score":0.04181927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07432450872731808,"score_gpt":0.271024070005763,"score_spread":0.1966995612784449,"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."}}