{"id":"W4301670286","doi":"10.1002/cjas.1424","title":"Acknowledgements – Remerciements","year":2016,"lang":"fr","type":"article","venue":"Canadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l Administration","topic":"Legal and Policy Issues","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Acknowledgement; Citation; Library science; Computer science; Computer security","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":["sts"],"category_scores_codex":[0.006567292,0.0004531822,0.0005423923,0.0007874452,0.004154241,0.0008259765,0.002051194,0.0002975107,0.006575406],"category_scores_gemma":[0.003975413,0.0003624247,0.0002865808,0.00290529,0.02712112,0.003249497,0.00003580582,0.0003269355,0.0003655966],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00324099,"about_ca_system_score_gemma":0.02916452,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02600666,"about_ca_topic_score_gemma":0.8332552,"domain_scores_codex":[0.9942212,0.0009368531,0.00120058,0.000692249,0.0005961228,0.002353009],"domain_scores_gemma":[0.9929917,0.0005270853,0.001103988,0.0002491634,0.001509412,0.003618598],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001324414,0.000414181,0.09216042,0.0003662347,0.0003310749,0.00209297,0.2136225,0.0001089548,0.002231723,0.5166141,0.06053761,0.1113878],"study_design_scores_gemma":[0.001039673,0.01255788,0.01247531,0.00305743,0.0002398243,0.001190754,0.03701136,0.0001229372,0.003358111,0.1149427,0.8126516,0.001352386],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.834963,0.004339603,0.000563002,0.03553632,0.007972576,0.0003699933,0.0002627599,0.00001562834,0.1159771],"genre_scores_gemma":[0.9580849,0.0005244064,0.003793745,0.0005122083,0.002088682,0.000007691925,0.00000195007,0.00001851554,0.03496794],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8072485,"threshold_uncertainty_score":0.9998828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1691454788311738,"score_gpt":0.3902227034557423,"score_spread":0.2210772246245685,"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."}}