{"id":"W6894277435","doi":"10.5683/sp3/jqwac1","title":"Kaladar Ontario. 1:50,000. Map Sheet 031C11, ed. 3, 1979","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); Digital mapping; Geographic information system; Aerial photography; Orthophoto","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":[0.0004299972,0.0018352,0.001383957,0.005393638,0.001604688,0.003291305,0.00177711,0.0005820781,0.1595178],"category_scores_gemma":[0.002684026,0.0009838879,0.0006449734,0.02166745,0.0004838788,0.001277133,0.001113383,0.001005745,0.1483839],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009580656,"about_ca_system_score_gemma":0.01563212,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.888068,"about_ca_topic_score_gemma":0.938604,"domain_scores_codex":[0.9992902,0.00002949656,0.00005716755,0.0001622357,0.0002989911,0.0001617928],"domain_scores_gemma":[0.9980149,0.0001251058,0.0001780878,0.0002502957,0.001218881,0.0002126403],"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":[0.00001688959,0.000003261177,0.0006204929,0.0002889538,0.000007982745,0.00001152635,0.00003878563,0.00006259979,0.00004233525,0.0002388562,0.9954201,0.003248253],"study_design_scores_gemma":[0.0000238414,0.000002355579,0.008025659,0.0001237371,0.000008025341,0.00001806019,0.0001025955,0.00006171805,0.00007946118,0.0001585343,0.9913828,0.00001332605],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005900351,0.00005253459,0.00002284599,0.00002224713,0.000009164025,0.000004507357,0.9974935,0.0001019471,0.002234311],"genre_scores_gemma":[0.0005169761,0.0001553974,0.0001817748,0.00001654619,0.000004967725,0.00003650749,0.9927951,0.0001061875,0.006186459],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1595178,"threshold_uncertainty_score":0.53364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01652472061431888,"score_gpt":0.2536616402107344,"score_spread":0.2371369195964155,"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."}}