{"id":"W4394491471","doi":"10.6084/m9.figshare.19127780","title":"Environmental and climatic metadata - feather moss nitrogen fixation and cyanobacterial biomass","year":2022,"lang":"en","type":"dataset","venue":"Figshare","topic":"Peatlands and Wetlands Ecology","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Moss; Metadata; Nitrogen fixation; Environmental science; Biomass (ecology); Feather; Periphyton; Nitrogen; Ecology; Biology; Chemistry; Computer science; World Wide Web","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":[0.000604381,0.001568742,0.001090785,0.004460843,0.00142219,0.001871984,0.002315684,0.00115922,0.03661535],"category_scores_gemma":[0.003789826,0.0006138289,0.000981914,0.01344752,0.0004181377,0.0008844478,0.001294988,0.001232704,0.01969452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007130669,"about_ca_system_score_gemma":0.01080588,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.8735465,"about_ca_topic_score_gemma":0.9316026,"domain_scores_codex":[0.999307,0.00005004161,0.00007265476,0.0001862168,0.0002098725,0.0001741861],"domain_scores_gemma":[0.9966977,0.0004225045,0.0002926296,0.0004183814,0.001837141,0.0003317395],"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":[0.00006677461,0.0000203119,0.007516513,0.00107446,0.00008539765,0.00005085146,0.00008165379,0.0009202926,0.0002448293,0.0008595784,0.9856358,0.003443487],"study_design_scores_gemma":[0.0001350786,0.000009674682,0.04916597,0.0005163308,0.00006558975,0.00005656773,0.0002215187,0.0009025031,0.0005159146,0.0007060519,0.9476423,0.00006259411],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001522846,0.00002119957,0.00001648786,0.00001329432,0.00000340858,0.00000321062,0.9995,0.00004662392,0.0002434642],"genre_scores_gemma":[0.0007122876,0.00003335904,0.0001303588,0.00001361285,0.000001448763,0.00002060063,0.9986677,0.00001920983,0.0004013913],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8735465,"threshold_uncertainty_score":0.2543963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01566697792930132,"score_gpt":0.2198639815864121,"score_spread":0.2041970036571108,"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."}}