{"id":"W6923971248","doi":"10.14288/1.0387569","title":"Index to the interim forest cover series and the forest inventory area reference system; Canada sheet 93 K/NW, K/SW","year":2019,"lang":"en","type":"other","venue":"Open Collections","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Forest inventory; Forest cover; Index (typography); Scale (ratio); Mile; Cover (algebra); Interim","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":[0.0002715554,0.0008870216,0.0004833994,0.004223354,0.0009791082,0.001304741,0.001060187,0.0002014449,0.2830553],"category_scores_gemma":[0.001726732,0.0003345525,0.0001483975,0.01356837,0.0002349117,0.0007406771,0.0005486748,0.0006261718,0.1907063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004010207,"about_ca_system_score_gemma":0.008773779,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7208045,"about_ca_topic_score_gemma":0.7493255,"domain_scores_codex":[0.9996604,0.00001719906,0.00002470423,0.0000478354,0.0001947414,0.00005515527],"domain_scores_gemma":[0.9982829,0.00008123399,0.00008338809,0.0001126146,0.001312603,0.0001272612],"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":[0.0000146623,0.000007415253,0.0003482666,0.00008604957,0.000001504826,0.000009293895,0.00003398139,0.00005112637,0.00004926453,0.0003961294,0.9771707,0.02183146],"study_design_scores_gemma":[0.00001018215,0.000004877175,0.01005177,0.00005742665,0.000002381894,0.00002017852,0.00007848522,0.0001052025,0.00008833685,0.0001872663,0.9893854,0.000008546796],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0008176682,0.0002911972,0.000414428,0.0001566836,0.0001548297,0.00024132,0.8500808,0.0009175891,0.1469254],"genre_scores_gemma":[0.006141722,0.0009460817,0.002138164,0.00009894429,0.00006177785,0.0003254869,0.7186081,0.0009017,0.2707781],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.2830553,"threshold_uncertainty_score":0.9469144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02578109799808014,"score_gpt":0.2438983059770823,"score_spread":0.2181172079790021,"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."}}