{"id":"W7034842684","doi":"","title":"Yhteisöllisen asumisen merkitys ikääntyneelle : Asukkaiden kokemuksia Wilhelmiina Tenholasta","year":2025,"lang":"fi","type":"other","venue":"","topic":"Numerical Methods and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Data collection; State (computer science); Set (abstract data type); Quarter (Canadian coin)","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":[0.000452664,0.0005692247,0.0005381725,0.0007543094,0.001455681,0.0026051,0.0005182402,0.0007712888,0.02018836],"category_scores_gemma":[0.0003994255,0.0002644581,0.0005146735,0.0006936398,0.0005145643,0.001185912,0.001237343,0.001320747,0.004894489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001420666,"about_ca_system_score_gemma":0.001819779,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008582353,"about_ca_topic_score_gemma":0.02778229,"domain_scores_codex":[0.9995796,0.0000452417,0.00002115544,0.00009370838,0.0001785576,0.0000817548],"domain_scores_gemma":[0.9996376,0.0000483329,0.00004841478,0.00001648209,0.0001674865,0.00008172274],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"qualitative","study_design_scores_codex":[0.001804568,0.0006536176,0.01478781,0.002770116,0.0001142674,0.003207114,0.005952985,0.0007004918,0.6795583,0.006029855,0.01469896,0.2697218],"study_design_scores_gemma":[0.00005095029,0.000784744,0.03791466,0.0004839283,0.0001595907,0.001851404,0.00688395,0.0004700223,0.1922766,0.001669947,0.7573509,0.0001032989],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6822232,0.03057222,0.01424715,0.006469417,0.002005925,0.0005101554,0.004249431,0.001093019,0.2586295],"genre_scores_gemma":[0.6418923,0.01281081,0.01714667,0.001384844,0.0002029731,0.0002300057,0.003235443,0.0004346021,0.3226624],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02018836,"threshold_uncertainty_score":0.06753677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01727355599942828,"score_gpt":0.2833779594071583,"score_spread":0.2661044034077301,"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."}}