{"id":"W6962400011","doi":"10.1594/pangaea.959412","title":"Raw herbaceous layer projective vegetation cover at 32 sites in Northwestern Canada, in Summer 2022 (CA-Land_2022_NWCanada)","year":2023,"lang":"en","type":"dataset","venue":"Publishing Network for Geoscientific and Environmental Data (PANGAEA) (Alfred Wegener Institute for Polar and Marine Research)","topic":"Historical, Literary, and Cultural Studies","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Vegetation (pathology); Quadrat; Taiga; Biome; Boreal; Herbaceous plant; Moss; Vegetation type","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":["metaepi_narrow","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001242294,0.0003961963,0.0004884824,0.0002833006,0.001830287,0.001048401,0.0006728711,0.0001723272,0.00012469],"category_scores_gemma":[0.0001464688,0.0003434997,0.0000707237,0.0002329892,0.0006014871,0.001395682,0.001552085,0.0005729317,0.00001468612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007394145,"about_ca_system_score_gemma":0.0002007213,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.993622,"about_ca_topic_score_gemma":0.9998446,"domain_scores_codex":[0.9965828,0.0001332609,0.0004953933,0.001083332,0.0007537315,0.0009514832],"domain_scores_gemma":[0.9987991,0.0002375628,0.0001487604,0.0005478754,0.00005047532,0.0002162185],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001305496,0.00009165871,0.002340062,0.0003417632,0.00009423806,0.00002972992,0.0009024985,0.00007063938,0.000003495899,0.0001185996,0.9944291,0.001447728],"study_design_scores_gemma":[0.0006929766,0.00008542823,0.002403784,0.00008553493,0.00005761323,0.000004563027,0.0007646988,0.0004756155,8.69971e-7,0.0001038166,0.9949046,0.0004205154],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.006650864,0.00367899,0.000003173921,0.0003227094,0.002023443,0.001225403,0.9857309,0.00001513207,0.0003494228],"genre_scores_gemma":[0.00284968,0.001939581,0.00002296577,0.0001375809,0.0008772017,0.0002579452,0.9732463,0.0000420792,0.02062671],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02027729,"threshold_uncertainty_score":0.9999886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0810855521286833,"score_gpt":0.2686284136510332,"score_spread":0.1875428615223499,"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."}}