{"id":"W4411913265","doi":"10.3389/fenvs.2025.1610130","title":"An innovation of two established methods for monitoring water colour and clarity: participatory science using the mini- and midi- secchi disks","year":2025,"lang":"en","type":"article","venue":"Frontiers in Environmental Science","topic":"Water Quality Monitoring Technologies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"UK Research and Innovation","keywords":"CLARITY; MIDI; Environmental science; Citizen journalism; Remote sensing; Computer science; Geography; Biology; World Wide Web","routes":{"ca_aff":true,"ca_fund":false,"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":["sts"],"consensus_categories":[],"category_scores_codex":[0.004216215,0.0001505404,0.0001864214,0.0002745742,0.0006200756,0.0001263529,0.0007500983,0.00006289656,0.000003528051],"category_scores_gemma":[0.0001641452,0.0001090301,0.00001477962,0.001020637,0.007199033,0.001137334,0.0009245923,0.0001569999,2.427252e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005227739,"about_ca_system_score_gemma":0.00002967034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000184474,"about_ca_topic_score_gemma":0.000005083785,"domain_scores_codex":[0.9980776,0.0001032816,0.0003327913,0.0006131019,0.0003687766,0.0005044187],"domain_scores_gemma":[0.9993524,0.00006316184,0.00009397377,0.0004217516,0.000007634795,0.000061074],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000009311827,0.00003288667,0.469585,0.000006229873,0.00000174609,2.112074e-7,0.0007744099,0.000275671,0.5162807,0.00007790433,0.00000371507,0.01295219],"study_design_scores_gemma":[0.0002556769,0.00005499011,0.3291462,0.00002000557,0.00001327345,0.000001321247,0.002499986,0.01378839,0.648341,0.005647287,0.00009969353,0.0001322053],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9789092,0.00008180153,0.01984902,0.0001524799,0.0005431163,0.0004087774,0.000004099716,0.00002335183,0.00002817789],"genre_scores_gemma":[0.8025006,0.00001414583,0.1974009,0.0000222362,0.000009902012,0.00003304742,5.73505e-7,0.000005497513,0.00001312151],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1775519,"threshold_uncertainty_score":0.9955028,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05236107310469703,"score_gpt":0.3763333211039365,"score_spread":0.3239722479992395,"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."}}