{"id":"W6950536669","doi":"10.5683/sp3/0xqdra","title":"Arundel Ontario. 1:50,000. Map Sheet 031G15, ed. 4, 1993","year":2021,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Georeference; General partnership; Raster graphics; Natural (archaeology); Aerial photography; Government (linguistics); Digital mapping; 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":[0.0005131111,0.002066072,0.001446149,0.005226458,0.001358285,0.002942187,0.002204484,0.0006240928,0.1881542],"category_scores_gemma":[0.002864098,0.0008383332,0.0007191035,0.02099156,0.0003420982,0.001048672,0.0008624907,0.001071742,0.1522104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009099236,"about_ca_system_score_gemma":0.01254066,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9165475,"about_ca_topic_score_gemma":0.9425522,"domain_scores_codex":[0.9992842,0.00004051806,0.00005040208,0.0001751067,0.0002780365,0.0001717249],"domain_scores_gemma":[0.9977836,0.0001476044,0.0001617775,0.0002674545,0.001429644,0.0002099516],"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":[0.00001317138,0.000003405458,0.0004936531,0.000169412,0.000007545842,0.000007839545,0.00001636538,0.00006840112,0.00002627027,0.0001566165,0.9955704,0.00346699],"study_design_scores_gemma":[0.00003356655,0.000003193855,0.01011907,0.0001509263,0.00001022135,0.0000175407,0.00009664986,0.0001263607,0.00009161531,0.0001676176,0.9891658,0.00001733663],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005123795,0.00004411435,0.00002034675,0.00001891667,0.000008181686,0.000004670475,0.9981195,0.00010034,0.001632648],"genre_scores_gemma":[0.0004900439,0.000117205,0.0001868091,0.00001952532,0.00000431592,0.00003869181,0.9934726,0.00008559743,0.005585277],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1881542,"threshold_uncertainty_score":0.6294385,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02024005424957009,"score_gpt":0.2604939253908855,"score_spread":0.2402538711413154,"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."}}