{"id":"W6931940681","doi":"10.5683/sp3/zyiq2u","title":"Mapping the Unseen: Identifying Data Gaps and Proposing New Sampling Points in Northern Boreal Mountain Eco-province, BC Using K-Means Clustering and cLHS","year":2024,"lang":"en","type":"dataset","venue":"Borealis","topic":"Marine and environmental studies","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Representativeness heuristic; Sampling (signal processing); Wetland; Boreal; Cluster analysis; Soil water; Resource (disambiguation); Principal component analysis; Soil map","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001560206,0.0004728887,0.0004084311,0.001696563,0.00123813,0.001280974,0.001538323,0.0004966931,0.001659855],"category_scores_gemma":[0.006307116,0.0002361356,0.0003050777,0.004892899,0.0005316723,0.0003900078,0.001101819,0.0006492609,0.000885601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004219649,"about_ca_system_score_gemma":0.0072471,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8037329,"about_ca_topic_score_gemma":0.9349402,"domain_scores_codex":[0.9990969,0.0001714275,0.00007600436,0.0002534177,0.0002410717,0.0001612776],"domain_scores_gemma":[0.9982774,0.0003697709,0.0001587805,0.0002881147,0.0007815324,0.0001243927],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006158887,0.000288413,0.3066033,0.001705065,0.0002413889,0.0009280353,0.003952361,0.01358685,0.003482058,0.007110138,0.5143698,0.1471167],"study_design_scores_gemma":[0.0001852461,0.0000506455,0.3814815,0.0006295717,0.0001098921,0.0003050129,0.007797328,0.0251381,0.002428677,0.004083671,0.5776904,0.0001000208],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.2376569,0.001408536,0.008219885,0.001137188,0.00009229691,0.0002873125,0.7411671,0.001188999,0.008841719],"genre_scores_gemma":[0.1517646,0.0003715534,0.01944535,0.0001214382,0.00001284219,0.0003821443,0.8249112,0.0001173272,0.002873524],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1962671,"threshold_uncertainty_score":0.3948458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06552851587348593,"score_gpt":0.2658110592135705,"score_spread":0.2002825433400845,"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."}}