{"id":"W6894182998","doi":"10.5683/sp3/n5484i","title":"Long John Creek British Columbia. 1:50,000. Map Sheet 093B14, ed. 1, 1978","year":2022,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Georeference; General partnership; Natural (archaeology); Raster graphics; Topographic map (neuroanatomy); Government (linguistics); Aerial photography; Viewshed analysis","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":[0.0004071032,0.002071621,0.001628114,0.005931132,0.001644932,0.004155754,0.002030602,0.0007426218,0.1494832],"category_scores_gemma":[0.002748962,0.001074296,0.0005705723,0.02883782,0.0004120168,0.001260903,0.001079975,0.001483273,0.1400649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008021959,"about_ca_system_score_gemma":0.01576137,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8960995,"about_ca_topic_score_gemma":0.9338922,"domain_scores_codex":[0.9993603,0.00002847858,0.00005493417,0.0001608264,0.0002352422,0.0001601921],"domain_scores_gemma":[0.9976693,0.0001315305,0.000145183,0.000244711,0.001582885,0.0002264291],"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":[0.00001203841,0.000003023802,0.000382208,0.0001519631,0.00000564365,0.000008336828,0.00001362382,0.00005055445,0.00001865721,0.0001297372,0.9967518,0.002472332],"study_design_scores_gemma":[0.00003402071,0.000002738838,0.009284471,0.0002375537,0.00001102611,0.00001929484,0.0001305496,0.000111491,0.0001052846,0.0002377509,0.989805,0.00002086102],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000600362,0.00004904996,0.00001791522,0.00002101622,0.00001143865,0.000003700747,0.9980423,0.00009002657,0.001704402],"genre_scores_gemma":[0.0004402598,0.0001487383,0.0001362287,0.00001936779,0.000004060345,0.00003589599,0.9931791,0.00008713151,0.005949159],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1494832,"threshold_uncertainty_score":0.500071,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01284227869150617,"score_gpt":0.2449521891571141,"score_spread":0.2321099104656079,"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."}}