{"id":"W6913085424","doi":"10.5683/sp3/nqnnmw","title":"Muchalat Inlet (East) British Columbia. 1:50,000. Map Sheet 092E09, ed. 1, 1955","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; Orthophoto; Aerial photography; Topographic map (neuroanatomy); Viewshed analysis; Government (linguistics)","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":[0.0003363865,0.001608357,0.001074601,0.004670309,0.001615465,0.003592735,0.001493205,0.0005542662,0.1210404],"category_scores_gemma":[0.002119137,0.0007664479,0.0004600668,0.0207375,0.0003990299,0.0009833721,0.0009492062,0.001158199,0.08727562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008949062,"about_ca_system_score_gemma":0.01611415,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9451987,"about_ca_topic_score_gemma":0.9711472,"domain_scores_codex":[0.9995066,0.00002189909,0.00003947878,0.000130511,0.0001725412,0.0001289728],"domain_scores_gemma":[0.9983695,0.00007047744,0.0001001812,0.0001682108,0.001129854,0.0001617834],"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":[0.00001773186,0.000003865365,0.0007887977,0.0001895096,0.000009241604,0.00001353217,0.00002848461,0.00006271256,0.00003044497,0.0001924651,0.9944952,0.004167951],"study_design_scores_gemma":[0.0000246083,0.000002361616,0.01478399,0.000228691,0.0000105723,0.0000205313,0.0001978861,0.000091116,0.0001184579,0.0001717785,0.9843312,0.00001890346],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001671847,0.0001227449,0.00002783257,0.00003608545,0.00002282031,0.000007243851,0.9955962,0.0001226587,0.003897184],"genre_scores_gemma":[0.001615263,0.0002848216,0.0002346832,0.00003835613,0.000007150471,0.00004809648,0.9832458,0.0001293552,0.01439643],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1210404,"threshold_uncertainty_score":0.4049206,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01289943084865146,"score_gpt":0.2375537973988477,"score_spread":0.2246543665501963,"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."}}