{"id":"W3027382139","doi":"10.1017/s0954102020000243","title":"Detection and community-level identification of microbial mats in the McMurdo Dry Valleys using drone-based hyperspectral reflectance imaging","year":2020,"lang":"en","type":"article","venue":"Antarctic Science","topic":"Polar Research and Ecology","field":"Environmental Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Hyperspectral imaging; Microbial mat; Remote sensing; Spectral signature; Geology; Cyanobacteria; Paleontology; Bacteria","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":[0.0000960045,0.0002017626,0.0001153983,0.0009019768,0.0003684068,0.000373469,0.000252539,0.0001654616,0.0006318095],"category_scores_gemma":[0.0001413119,0.0001302368,0.00009590732,0.0005515169,0.0001678973,0.0001294509,0.0002354243,0.00015004,0.0001107646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004385056,"about_ca_system_score_gemma":0.0002458571,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06649348,"about_ca_topic_score_gemma":0.2320518,"domain_scores_codex":[0.9999195,0.000006477027,0.00000238594,0.00002646482,0.00002683563,0.00001825903],"domain_scores_gemma":[0.9999197,0.000008372941,0.00002148466,0.000004712403,0.00002274333,0.00002307902],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003189174,0.0000749458,0.6597301,0.00007563149,0.00009424608,0.0001899386,0.0008685557,0.0005306995,0.3113831,0.00006542508,0.0004622057,0.02620623],"study_design_scores_gemma":[0.000005814431,0.00002587806,0.9937186,0.000005382329,0.000007061624,0.00005540875,0.0003379593,0.0009036789,0.004382869,0.000008476488,0.0005445367,0.000004305173],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998904,0.00007421177,0.0002055815,0.000008701893,0.000001318271,0.000006676683,0.0002924961,0.000009434509,0.0004974852],"genre_scores_gemma":[0.9978067,0.00005504298,0.001171761,0.0000167826,0.000002329956,0.000009962713,0.0005175619,0.000003868834,0.0004159705],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06649348,"threshold_uncertainty_score":0.1322129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05385806431566056,"score_gpt":0.303009081492413,"score_spread":0.2491510171767524,"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."}}