{"id":"W4384930103","doi":"10.53555/sfs.v10i1.1037","title":"Environmental impacts on seasonal fish diversity in Jamuna River, Bangladesh","year":2023,"lang":"en","type":"article","venue":"Journal of Survey in Fisheries Sciences","topic":"Fish Biology and Ecology Studies","field":"Agricultural and Biological Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Canonical correspondence analysis; Species richness; Species evenness; Ecology; Abundance (ecology); Wet season; Biology; Biodiversity; Monsoon; Seasonality; Species diversity; River ecosystem; Diversity index; Fishery; Geography; Ecosystem","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001656029,0.0001364229,0.0001513897,0.0005523973,0.0005768693,0.0004512519,0.0001379757,0.0001681898,0.001230573],"category_scores_gemma":[0.0005831301,0.0001180846,0.000108646,0.001002105,0.0003528935,0.0002670295,0.0003936821,0.0001401389,0.0001484201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005557397,"about_ca_system_score_gemma":0.000352293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0215048,"about_ca_topic_score_gemma":0.05716134,"domain_scores_codex":[0.9998344,0.00003880353,0.00001852492,0.00003491201,0.00003058012,0.00004274286],"domain_scores_gemma":[0.9997341,0.00004796209,0.0000820014,0.00001243095,0.00006099896,0.00006249341],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001849202,0.00005239152,0.9778024,0.00005597445,0.00004513572,0.0006214907,0.002624491,0.0002235762,0.008183294,0.0001360789,0.0003162099,0.009753974],"study_design_scores_gemma":[0.000001897387,0.00003779789,0.9974054,0.000005619188,0.000005942454,0.00007917426,0.001985628,0.00008331248,0.00007059568,0.0000321409,0.0002872293,0.000005177103],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.999267,0.00004412242,0.00002867899,0.00002595048,0.000001070176,0.000002587376,0.0001342951,0.00000132748,0.0004950063],"genre_scores_gemma":[0.9996177,0.0000598322,0.000026901,0.000008045534,9.558859e-7,0.000004419146,0.000103372,7.152506e-7,0.0001780536],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0215048,"threshold_uncertainty_score":0.04275924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1415198091980244,"score_gpt":0.2413731530305943,"score_spread":0.09985334383256991,"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."}}