{"id":"W2923720657","doi":"10.15407/np.46.274","title":"Multicultural Digital Resources of the USA, Canada and Australia","year":2017,"lang":"en","type":"article","venue":"Naukovì pracì Nacìonalʹnoï bìblìoteki Ukraïni ìmenì V Ì Vernadsʹkogo","topic":"Water Resources and Governance","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Multiculturalism; Political science; Geography; Media studies; Library science; Telecommunications; Sociology; Computer science; Law","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":[0.0005608463,0.0001808333,0.0003329859,0.0047649,0.006787912,0.004548626,0.0006872097,0.0003631742,0.007319517],"category_scores_gemma":[0.002944859,0.0001743951,0.0001946481,0.01261347,0.001464102,0.00179808,0.003585228,0.000603157,0.0002884023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02514276,"about_ca_system_score_gemma":0.03687057,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9827819,"about_ca_topic_score_gemma":0.9958459,"domain_scores_codex":[0.9992861,0.00007114262,0.00002379198,0.00006418943,0.0002348939,0.00031982],"domain_scores_gemma":[0.9967615,0.0004122491,0.000353712,0.0001119672,0.00126141,0.001099191],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002836372,0.0002321444,0.5728858,0.0003714324,0.0001425001,0.001577083,0.1545255,0.0006706392,0.0008093584,0.03819735,0.02830205,0.2020025],"study_design_scores_gemma":[0.000004884151,0.00001947783,0.816209,0.0001353126,0.0000313133,0.0001632264,0.123748,0.0003479321,0.0001677387,0.0008352039,0.0582988,0.00003910212],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.955617,0.001053066,0.00008100891,0.001655038,0.0000151265,0.00003993074,0.002156263,0.00001765557,0.03936497],"genre_scores_gemma":[0.9849942,0.001139256,0.0001954796,0.0002335425,0.000004467261,0.00002031805,0.0007020057,0.00001183237,0.01269895],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02514276,"threshold_uncertainty_score":0.1824244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0289265165853294,"score_gpt":0.2890417187071044,"score_spread":0.260115202121775,"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."}}