{"id":"W4384701476","doi":"10.1016/j.softx.2023.101469","title":"FIPEX v10.4: An ArcGIS Desktop Add-in for assessing impacts of fish passage barriers and longitudinal connectivity of rivers","year":2023,"lang":"en","type":"article","venue":"SoftwareX","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Parks Canada; Memorial University of Newfoundland; University of British Columbia; Fisheries and Oceans Canada","funders":"Fisheries and Oceans Canada; Natural Sciences and Engineering Research Council of Canada; Dalhousie University; Parks Canada","keywords":"Biome; Computer science; Fish <Actinopterygii>; Environmental science; Environmental resource management; Hydrology (agriculture); Water resource management; Ecology; Fishery; Ecosystem; Geology","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.000474362,0.00009019724,0.0001957215,0.00006252599,0.0001212909,0.000007783968,0.00009988686,0.00005197227,0.0002095628],"category_scores_gemma":[0.0004924197,0.00009041421,0.00003462154,0.0002210685,0.0003204755,0.0003013247,0.0001784784,0.00005430134,0.00000341493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004900615,"about_ca_system_score_gemma":0.00001024478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002829705,"about_ca_topic_score_gemma":0.004323892,"domain_scores_codex":[0.9992334,0.00004458133,0.000147771,0.0002340596,0.0001030389,0.0002371887],"domain_scores_gemma":[0.9994122,0.00030317,0.00009170928,0.0001238634,0.000008012175,0.00006101131],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002640747,0.00002982696,0.988994,0.00006304518,0.00002291456,0.000005808311,0.0005184378,0.0001513663,0.000217284,0.00002927163,0.007960128,0.001981524],"study_design_scores_gemma":[0.0004641782,0.0001159342,0.9959106,0.00001879179,0.000021377,4.55376e-7,0.0006914723,0.000322371,0.0005088643,0.001652113,0.0002034559,0.00009036739],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983137,0.000005143464,0.0005134169,0.0002207054,0.0000593057,0.0002191171,0.00003906663,0.00003874941,0.0005908277],"genre_scores_gemma":[0.9991659,0.00002547703,0.000597055,0.0001084393,0.000005704224,0.00001920236,0.000007993786,0.000006764054,0.00006347799],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007756671,"threshold_uncertainty_score":0.3686984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02037442553433562,"score_gpt":0.2735400944782491,"score_spread":0.2531656689439135,"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."}}