{"id":"W6904840196","doi":"10.1371/journal.pone.0281980.g003","title":"Areas with high current densities over the density of ranges for species at risk in Canada [68].","year":2023,"lang":"en","type":"other","venue":"Figshare","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Current (fluid); Percentile; Government (linguistics); Population density","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":[0.0001506124,0.0003175472,0.0002031115,0.001542162,0.001982629,0.001146695,0.0007261885,0.0002641164,0.06253848],"category_scores_gemma":[0.0007986242,0.0001823155,0.0003973384,0.004247631,0.0003889893,0.0005015568,0.0006655269,0.0004561887,0.004028456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008577457,"about_ca_system_score_gemma":0.01644078,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9943663,"about_ca_topic_score_gemma":0.9984396,"domain_scores_codex":[0.9998204,0.00001002891,0.000005171151,0.00002747532,0.00005736717,0.00007964027],"domain_scores_gemma":[0.9996228,0.0000299759,0.0000244456,0.00001241515,0.0002348835,0.00007541821],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001318186,0.00002725171,0.06832586,0.0009959573,0.00008007044,0.0004118551,0.002594248,0.001710106,0.0006948673,0.009221203,0.81483,0.1009767],"study_design_scores_gemma":[0.00003756367,0.00001563977,0.4832574,0.001049894,0.0001070671,0.000628275,0.008276828,0.001810429,0.0004407119,0.001994146,0.5022775,0.0001046473],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.0817019,0.004700296,0.003010992,0.003230554,0.0003443727,0.0001815479,0.5685593,0.001435212,0.3368358],"genre_scores_gemma":[0.6767731,0.006226854,0.01262223,0.0009742539,0.00005327856,0.0001508718,0.1617439,0.000668733,0.1407868],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06253848,"threshold_uncertainty_score":0.2092121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03856336027764262,"score_gpt":0.2380649358259249,"score_spread":0.1995015755482823,"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."}}