{"id":"W3159386408","doi":"10.1093/biosci/biab018","title":"Connecting Top-Down and Bottom-Up Approaches in Environmental Observing","year":2021,"lang":"en","type":"article","venue":"BioScience","topic":"Indigenous Studies and Ecology","field":"Health Professions","cited_by":108,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Horizon 2020 Framework Programme; National Science Foundation","keywords":"Indigenous; Top-down and bottom-up design; Sustainability; Globe; Matching (statistics); Environmental resource management; Computer science; Knowledge management; Environmental planning; Process management; Business; Environmental science; Psychology","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":[0.000504548,0.00006219083,0.000117343,0.00002607539,0.001951827,0.000007416067,0.00008259257,0.00006966387,0.0001428365],"category_scores_gemma":[0.0001772555,0.00005644151,0.00001207285,0.0001232326,0.00006182521,0.00006404771,0.0003936492,0.0002056121,0.00003535256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001267185,"about_ca_system_score_gemma":0.000104504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003766063,"about_ca_topic_score_gemma":0.005559321,"domain_scores_codex":[0.9988526,0.0001040453,0.0001655059,0.0002583541,0.00007181414,0.000547641],"domain_scores_gemma":[0.999613,0.0001734591,0.00005068666,0.0001098123,0.000007972651,0.00004508764],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000005402188,0.00005695843,0.9106783,0.00006581451,0.000003697085,0.00002514585,0.07481485,0.000004217757,0.009661286,0.001339952,0.00008622617,0.003258165],"study_design_scores_gemma":[0.0005335023,0.00006159276,0.6185727,0.00005583981,0.000005228828,0.00001597968,0.3713303,0.001086028,0.0007303135,0.0001888158,0.007212975,0.0002066965],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946241,0.0004652088,0.00003333169,0.0009875763,0.0005304636,0.0001662891,0.000004471879,0.00001396566,0.003174624],"genre_scores_gemma":[0.9979548,0.0001211624,0.0006999353,0.000639436,0.0000539502,0.00001994233,0.000001880024,0.00000434876,0.0005044977],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2965155,"threshold_uncertainty_score":0.9993475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1153199445151299,"score_gpt":0.3413870948496132,"score_spread":0.2260671503344833,"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."}}