{"id":"W6977003602","doi":"10.6073/pasta/de796f76bc4aa7cbff001733805adf72","title":"Distribution models of microbial mats and mosses across Fryxell Basin, Taylor Valley, Antarctica (2018-2019)","year":2023,"lang":"en","type":"dataset","venue":"Environmental Data Initiative","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transect; Moss; Microbial mat; Quadrat; STREAMS; Biota; Abundance (ecology); Satellite imagery; Hydrology (agriculture)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003959425,0.0003263543,0.0001605581,0.0005844911,0.0004279983,0.0005845538,0.000689676,0.0004123008,0.00135576],"category_scores_gemma":[0.0006447097,0.0001959919,0.0004379424,0.0004817822,0.0003115887,0.0004022238,0.0003835208,0.0002431587,0.0002711869],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001857932,"about_ca_system_score_gemma":0.0007491386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1914153,"about_ca_topic_score_gemma":0.1685131,"domain_scores_codex":[0.9999231,0.00001044547,0.000003094724,0.00003088004,0.000008285774,0.00002410255],"domain_scores_gemma":[0.9997187,0.00006738068,0.00007573235,0.00002143561,0.0000616621,0.00005513793],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003273173,0.00008093585,0.7721011,0.00005241998,0.0001023357,0.0002350531,0.0003985944,0.201127,0.003339471,0.001819037,0.002725791,0.01769087],"study_design_scores_gemma":[0.00005528107,0.00007606666,0.3309709,0.00002755961,0.00005528835,0.0001526352,0.0006211682,0.6641719,0.0008892649,0.001297641,0.001656532,0.00002564961],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.9968593,0.00009577124,0.001083225,0.0001309852,0.000003842478,0.00001096264,0.001070977,0.00004391071,0.0007009644],"genre_scores_gemma":[0.9972529,0.00006593914,0.0008038896,0.00002242215,0.000004606155,0.00001946594,0.001197208,0.000009744705,0.0006237509],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.1914153,"threshold_uncertainty_score":0.3806023,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06053856779311845,"score_gpt":0.2948386616299713,"score_spread":0.2343000938368529,"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."}}