{"id":"W2999377562","doi":"10.1002/hyp.13700","title":"Modifying the Jackson index to quantify the relationship between geology, landscape structure, and water transit time in steep wet headwaters","year":2020,"lang":"en","type":"article","venue":"Hydrological Processes","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Global Institute for Water Security; University of Saskatchewan","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Hydrology (agriculture); Bedrock; Geology; Drainage basin; Water content; Soil water; Geomorphology; Physical geography; Soil science; Geography; Geotechnical engineering; Cartography","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":[0.0003036207,0.0001653111,0.0002046107,0.00002480207,0.0003622401,0.0000321442,0.0003211798,0.0001197808,0.0003445209],"category_scores_gemma":[0.0001679127,0.00007192371,0.00002188918,0.0002469359,0.0004199209,0.0001227191,0.0003389968,0.0003175941,0.0002348643],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001016641,"about_ca_system_score_gemma":0.00000230007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005347237,"about_ca_topic_score_gemma":0.0001114997,"domain_scores_codex":[0.9987515,0.0001527336,0.0002013733,0.000385782,0.000146362,0.0003622676],"domain_scores_gemma":[0.999402,0.0003713513,0.00002976057,0.0001225898,0.000004334211,0.00006999152],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007765619,0.0000101106,0.9800109,0.00002548909,0.00001436305,0.000006665049,0.002872733,0.01633103,0.0001279088,0.00002746578,0.0003577408,0.0001379455],"study_design_scores_gemma":[0.0003610627,0.000198624,0.9873267,0.000005599593,0.00003156806,0.000003310083,0.0001480799,0.002326172,0.0003117351,0.006657068,0.002447968,0.0001821483],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9265513,0.00006938482,0.0003036211,0.0721237,0.00001406103,0.0003356345,0.000003662695,0.00004328067,0.0005553263],"genre_scores_gemma":[0.994557,0.00001142793,0.00002720267,0.00525258,0.00003703863,0.00002942618,0.00001017042,0.000007219075,0.00006792339],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06800568,"threshold_uncertainty_score":0.3772262,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0406341325651098,"score_gpt":0.2468411918583686,"score_spread":0.2062070592932588,"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."}}