{"id":"W2291147643","doi":"10.1080/09658211.2015.1046382","title":"Spatial part-set cuing facilitation","year":2015,"lang":"en","type":"article","venue":"Memory","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Psychology; Facilitation; Cognitive psychology; Set (abstract data type); Cognitive science; Neuroscience; Computer science","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":[0.000567611,0.0007422433,0.000629439,0.0004209563,0.0004246237,0.0005751309,0.001029107,0.0005114707,0.007118638],"category_scores_gemma":[0.00891047,0.0004316307,0.0004121149,0.0002425497,0.0006602451,0.001028328,0.002033303,0.001107814,0.0005694441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006401287,"about_ca_system_score_gemma":0.0006229921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005565672,"about_ca_topic_score_gemma":0.004875107,"domain_scores_codex":[0.9993039,0.00009116621,0.00005905622,0.0002262074,0.0002399524,0.00007968755],"domain_scores_gemma":[0.9950465,0.002229516,0.0004040563,0.001248146,0.0006537352,0.0004181245],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.002274375,0.0004108742,0.005602098,0.0008937971,0.00008387685,0.0002779776,0.001139002,0.001108571,0.8594264,0.005915127,0.001453287,0.1214145],"study_design_scores_gemma":[0.0008650451,0.005627431,0.3339915,0.0004210187,0.0005221824,0.002260755,0.0009956417,0.02728545,0.5808578,0.02262458,0.02426597,0.000282581],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9361017,0.002322831,0.03367462,0.0002187545,0.000382919,0.0002554615,0.0004239012,0.001003108,0.02561678],"genre_scores_gemma":[0.9888417,0.0002985752,0.007911331,0.0001300687,0.00002487345,0.0001069433,0.0001592995,0.0001425349,0.00238472],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007118638,"threshold_uncertainty_score":0.0238142,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02804682044997232,"score_gpt":0.2241002231976536,"score_spread":0.1960534027476812,"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."}}