{"id":"W6992052045","doi":"","title":"Kiinalaiset matkailijat Kouvolassa – yritysten valmiudet, odotukset ja kehittämistarpeet","year":2018,"lang":"fi","type":"other","venue":"Theseus (Ammattikorkeakoulujen)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Statistical analysis; Quarter (Canadian coin); Research methodology; Unemployment","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":[0.00128037,0.0006805061,0.0005797778,0.000921255,0.003606119,0.006531831,0.001086813,0.001420066,0.1122392],"category_scores_gemma":[0.002128631,0.0005690421,0.0006995598,0.0008460218,0.001717696,0.003632042,0.005033851,0.002807533,0.04530912],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002675206,"about_ca_system_score_gemma":0.004080683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004600853,"about_ca_topic_score_gemma":0.01542651,"domain_scores_codex":[0.9987711,0.0001551354,0.00005441078,0.0003089709,0.0004674705,0.00024287],"domain_scores_gemma":[0.9983663,0.0002190436,0.000144726,0.0001882732,0.0005661326,0.0005155129],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001410606,0.0005681568,0.02590751,0.002263811,0.0001326515,0.002218845,0.03359672,0.0009820324,0.09143183,0.1721574,0.207318,0.4620124],"study_design_scores_gemma":[0.00001248929,0.00009513205,0.008572776,0.0001888903,0.00001915013,0.0003637843,0.003555983,0.0001648773,0.006895978,0.003944696,0.9761411,0.00004522672],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.09062663,0.005992589,0.01613241,0.009991234,0.004039726,0.0002071069,0.001727923,0.001804427,0.8694779],"genre_scores_gemma":[0.1600241,0.002794646,0.01213523,0.001383736,0.0004544882,0.0001596105,0.001427884,0.001565582,0.8200547],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1122392,"threshold_uncertainty_score":0.3754774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02352233090583188,"score_gpt":0.2649173125975204,"score_spread":0.2413949816916885,"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."}}