{"id":"W6912923007","doi":"10.5683/sp3/v0pgnq","title":"Sunny Bank (West) Quebec. 1:50,000. Map Sheet 022A15, ed. 1, 1957","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; Aerial photography; Raster graphics; Natural (archaeology); Viewshed analysis; Government (linguistics); Orthophoto; Geographic information system","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":[0.000479368,0.001896067,0.001256429,0.004473119,0.001788582,0.003437989,0.001963328,0.0007251356,0.1842201],"category_scores_gemma":[0.002705309,0.0007430189,0.0007180774,0.01883919,0.0004572396,0.001136105,0.0009093574,0.001268459,0.1066961],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01279355,"about_ca_system_score_gemma":0.01932913,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9715708,"about_ca_topic_score_gemma":0.9839327,"domain_scores_codex":[0.999358,0.00003124086,0.00003619945,0.0001548292,0.0002352283,0.0001844075],"domain_scores_gemma":[0.9978107,0.00009560463,0.0001180411,0.0002203053,0.001557773,0.0001977669],"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":[0.00001511562,0.000003961683,0.000739218,0.000133844,0.000008554275,0.000009347043,0.00001998973,0.00006994382,0.00002501532,0.0002230199,0.995438,0.003314142],"study_design_scores_gemma":[0.00003990802,0.000003302251,0.01364523,0.0002105695,0.000009828455,0.00001897757,0.0001278107,0.0001478041,0.00009377576,0.000197137,0.9854836,0.00002196259],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009655753,0.0000815774,0.00003382516,0.00003371985,0.00002154562,0.000007941155,0.9965654,0.0001245209,0.003034857],"genre_scores_gemma":[0.001418538,0.0001890456,0.0002802882,0.00005012965,0.000009005013,0.00005230646,0.9872759,0.0001492237,0.01057542],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1842201,"threshold_uncertainty_score":0.6162776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01681191646962497,"score_gpt":0.2670560403660582,"score_spread":0.2502441238964332,"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."}}