{"id":"W6886042663","doi":"10.14288/1.0373195","title":"Community - Based Water Monitoring : Build Your Own Water Monitoring Logger","year":2018,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Water Quality Monitoring Technologies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Data logger; Global Positioning System; Logging; Data collection; Assisted GPS; Citizen science; Proxy (statistics); Indigenous","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006614098,0.0001075792,0.0002961956,0.00005474085,0.001040133,0.0001564167,0.001208383,0.0002335222,0.0004358756],"category_scores_gemma":[0.00003319195,0.0002396065,0.0001261482,0.0001857347,0.001201795,0.0006075779,0.001414255,0.0004648825,0.0005616906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004346239,"about_ca_system_score_gemma":0.000009451115,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2246184,"about_ca_topic_score_gemma":0.01587147,"domain_scores_codex":[0.9980066,0.0002034595,0.0002000624,0.0004520539,0.0004623913,0.0006753916],"domain_scores_gemma":[0.9987911,0.00004223441,0.00007572863,0.0008836748,0.00006816396,0.0001390944],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002391439,0.0002802527,0.7928928,0.00007012951,0.00004548165,0.0001007847,0.00189526,0.00005455303,0.111981,1.414024e-7,0.001338047,0.09131759],"study_design_scores_gemma":[0.0006227233,0.0001650865,0.9515154,0.0001386432,0.00003267374,0.00001407968,0.002816951,0.00003990459,0.04173439,0.0003537072,0.002192503,0.0003739299],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973986,0.000008555771,0.0002076816,0.0002559593,0.0006359313,0.0001879193,0.00002364965,0.0004071862,0.0008745425],"genre_scores_gemma":[0.9957063,0.00001014528,0.003043152,0.00001457853,0.0001468009,0.000001546286,0.00001000469,0.0000287581,0.001038777],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.208747,"threshold_uncertainty_score":0.9770868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02963611369668137,"score_gpt":0.2148514143535577,"score_spread":0.1852153006568764,"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."}}