{"id":"W6969029188","doi":"10.5683/sp3/n4gaj4","title":"Codys (East) New Brunswick. 1:50,000. Map Sheet 021H13, ed. 1, 1951","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; Raster graphics; Natural (archaeology); Aerial photography; Digital mapping; Government (linguistics); Geographic information system; 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":[0.0006087654,0.002182441,0.001380608,0.005838956,0.00105149,0.003673621,0.002347062,0.0006521934,0.1583393],"category_scores_gemma":[0.003264518,0.001116437,0.0007240035,0.02079817,0.0004122409,0.001626476,0.001441073,0.001333798,0.1702651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006067854,"about_ca_system_score_gemma":0.01151751,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7486143,"about_ca_topic_score_gemma":0.8495218,"domain_scores_codex":[0.9992701,0.00004002521,0.00007915709,0.0002031247,0.00023813,0.0001693918],"domain_scores_gemma":[0.9979022,0.0001433598,0.0001900984,0.0003700449,0.001216155,0.0001782444],"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":[0.00001788522,0.000003331231,0.0005559953,0.0002590803,0.00001009131,0.00001491726,0.00002907371,0.00007496089,0.00006072266,0.0002955549,0.9948442,0.003834189],"study_design_scores_gemma":[0.00002235733,0.000001625466,0.003785464,0.000154101,0.000005665684,0.00001647112,0.00009392001,0.0000434361,0.0001061851,0.0001882962,0.9955681,0.00001438756],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005661085,0.00006161151,0.0000300345,0.00002326828,0.00002057576,0.000005681607,0.9976819,0.000148923,0.001971303],"genre_scores_gemma":[0.0003864558,0.0001371772,0.0002311569,0.00002698126,0.000004434736,0.00003454255,0.9939765,0.000185811,0.005016895],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2513857,"threshold_uncertainty_score":0.5296976,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01870062347551365,"score_gpt":0.2626862414990416,"score_spread":0.243985618023528,"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."}}