{"id":"W4410514858","doi":"10.18280/ijdne.200405","title":"Assessment of Pollution Risks in the Kufa River Using Water Quality Indices and Principal Component Analysis","year":2025,"lang":"en","type":"article","venue":"International Journal of Design & Nature and Ecodynamics","topic":"Water Resources and Management","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Principal component analysis; Environmental science; Pollution; Water quality; Water resource management; Quality (philosophy); River pollution; Environmental engineering; Statistics; Mathematics","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":[0.0009871284,0.00006619219,0.000139729,0.0002112332,0.00003846949,0.00004408362,0.0002186237,0.00005362751,0.00001772503],"category_scores_gemma":[0.000008004097,0.00003875665,0.00005733618,0.0001274721,0.00007429298,0.0001281533,0.0001395666,0.0001986053,1.520171e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001149433,"about_ca_system_score_gemma":0.000006438163,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004957877,"about_ca_topic_score_gemma":0.0001786255,"domain_scores_codex":[0.999063,0.000122281,0.0003070745,0.00009407712,0.0003332848,0.00008033511],"domain_scores_gemma":[0.999667,0.0000443616,0.0001878124,0.00005932486,0.00002249573,0.0000190351],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000127752,0.0002243718,0.7933708,0.00001881767,0.001091015,0.00003453448,0.002336525,0.1926928,0.004872427,0.001757674,0.00002236651,0.003450844],"study_design_scores_gemma":[0.0003407698,0.00003094041,0.9331829,0.00002013593,0.0001548039,0.000008267253,0.0002032909,0.06417572,0.0001287251,0.001368845,0.0003375966,0.00004803693],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9724214,0.00008407902,0.02652191,0.0005933102,0.00009042884,0.00007326537,0.000004506877,9.728857e-7,0.0002101153],"genre_scores_gemma":[0.9971293,0.0001016292,0.002508333,0.0002275013,0.0000147785,6.210552e-7,0.000003469267,0.000001654789,0.0000127658],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.139812,"threshold_uncertainty_score":0.1580451,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02397835849018603,"score_gpt":0.326988652829668,"score_spread":0.303010294339482,"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."}}