{"id":"W4254204276","doi":"10.18356/3195865b-en","title":"Acknowledgements","year":2019,"lang":"en","type":"book-chapter","venue":"","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Task force; Kingdom; Political science; Humanities; Economic history; History; Art; Public administration","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.004200163,0.0008673597,0.001018993,0.002796856,0.00206221,0.00365024,0.002344564,0.001419295,0.3909074],"category_scores_gemma":[0.0306074,0.000291444,0.0005553661,0.002627403,0.0008686276,0.003043736,0.004059251,0.002708001,0.2518107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002930072,"about_ca_system_score_gemma":0.00429597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003263281,"about_ca_topic_score_gemma":0.004925382,"domain_scores_codex":[0.9957142,0.0009474708,0.0003290116,0.0005628259,0.002170967,0.0002754456],"domain_scores_gemma":[0.9792837,0.003098667,0.0006405303,0.001664468,0.01317969,0.002132879],"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":[0.00002861931,0.00001230185,0.0002152388,0.0001941482,0.000003402958,0.000147654,0.000573724,0.00004840189,0.0001471381,0.01333992,0.946657,0.03863243],"study_design_scores_gemma":[0.000002427188,0.000003526153,0.0001404541,0.0001082815,0.000001424317,0.00009291101,0.0002685727,0.00001955576,0.00003470629,0.001392091,0.9979331,0.000002879664],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.003792217,0.01122666,0.01304384,0.09731754,0.09064087,0.001137131,0.05166369,0.002405674,0.7287723],"genre_scores_gemma":[0.01632532,0.004744023,0.009777264,0.01449617,0.007010223,0.001043894,0.02183305,0.00238,0.92239],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.6090926,"threshold_uncertainty_score":0.8687967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02438042760638836,"score_gpt":0.2970876464372463,"score_spread":0.272707218830858,"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."}}