{"id":"W2122869775","doi":"10.1515/mfir.2003.27","title":"Digitization of Cartographic Materials: National Archives of Canada","year":2003,"lang":"en","type":"article","venue":"Microform and Imaging Review","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Digitization; Geography; Microform; National archives; Archaeology; Library science; Cartography; History; Computer science; Telecommunications","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":[0.001882943,0.0005095131,0.000409059,0.01182858,0.005946388,0.005838781,0.001303779,0.0007298159,0.02020596],"category_scores_gemma":[0.005123345,0.0004097305,0.0002896849,0.03890242,0.001566966,0.001646946,0.001272803,0.0009148133,0.004083212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06853916,"about_ca_system_score_gemma":0.1830683,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9911211,"about_ca_topic_score_gemma":0.9950731,"domain_scores_codex":[0.9966542,0.0001553353,0.0001729094,0.0002074665,0.002510344,0.0002998601],"domain_scores_gemma":[0.9909518,0.0002588976,0.0002825089,0.000243254,0.00788109,0.0003825455],"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":[0.00003932686,0.00002016996,0.005351299,0.001497064,0.00001427817,0.0001714018,0.001868951,0.0003496974,0.000514067,0.01977675,0.6680226,0.3023745],"study_design_scores_gemma":[0.000002134005,0.000003617054,0.01361315,0.0004410644,0.00001007159,0.00007208159,0.0007545105,0.00005889966,0.0001812573,0.0004199196,0.9844273,0.00001604693],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01608983,0.2537329,0.002882062,0.0313707,0.002931706,0.0008205175,0.06892452,0.0008450507,0.6224027],"genre_scores_gemma":[0.1241601,0.3595004,0.01451431,0.004905713,0.0006685527,0.0004544435,0.04920325,0.0004442861,0.446149],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.06853916,"threshold_uncertainty_score":0.4972888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008898645070764825,"score_gpt":0.2493255536316578,"score_spread":0.240426908560893,"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."}}