{"id":"W6922231579","doi":"10.1051/bioconf/202414006006/pdf","title":"Referral programs as a referral recruiting tool","year":2024,"lang":"en","type":"article","venue":"Springer Link (Chiba Institute of Technology)","topic":"Educational Robotics and Engineering","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Referral; Patient referral; Quarter (Canadian coin); Factory (object-oriented programming); MEDLINE","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":[0.01672875,0.0006519082,0.0005172508,0.005833658,0.002427686,0.003170827,0.002210984,0.001547761,0.008296916],"category_scores_gemma":[0.03929524,0.0004354234,0.0004958924,0.00264491,0.001161549,0.002667756,0.003487769,0.001159805,0.003935953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001357271,"about_ca_system_score_gemma":0.00404464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006536741,"about_ca_topic_score_gemma":0.001786066,"domain_scores_codex":[0.9723662,0.02089533,0.001042456,0.001065177,0.003726706,0.0009042235],"domain_scores_gemma":[0.9530019,0.02751575,0.005488654,0.003585367,0.006139923,0.004268555],"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":[0.0002984495,0.002462483,0.01825524,0.0009170414,0.00002628429,0.0003987578,0.006659915,0.0008546274,0.005545945,0.00509311,0.01520929,0.9442788],"study_design_scores_gemma":[0.0009709159,0.01945656,0.182581,0.007250735,0.0006558494,0.01034024,0.05388055,0.07579466,0.05774168,0.02234305,0.5678734,0.001111329],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.526414,0.001651491,0.29908,0.00811474,0.0007854432,0.008845435,0.000435912,0.01983547,0.1348375],"genre_scores_gemma":[0.5726976,0.0009151235,0.3943328,0.002063006,0.0002383322,0.002966246,0.0004794205,0.0004821735,0.02582521],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01672875,"threshold_uncertainty_score":0.08847111,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03496951271241418,"score_gpt":0.2777409764137995,"score_spread":0.2427714637013854,"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."}}