{"id":"W2944296397","doi":"10.15353/cjo.78.462","title":"Patient Acquisition in Today’s Busy Digital World","year":2016,"lang":"en","type":"article","venue":"Canadian journal of optometry/CJO. Canadian journal of optometry","topic":"AI in Service Interactions","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","bibliometrics","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001202342,0.0005135113,0.0008990093,0.01528145,0.0003174899,0.001160559,0.002766652,0.0002601203,0.0008865698],"category_scores_gemma":[0.0006051509,0.0004298548,0.0005487099,0.006136145,0.0002610561,0.005612927,0.00008046366,0.001189807,0.0001282652],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.00388078,"about_ca_system_score_gemma":0.007273796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0025627,"about_ca_topic_score_gemma":0.009951808,"domain_scores_codex":[0.9946202,0.0002060271,0.00221866,0.0004264912,0.001039305,0.001489292],"domain_scores_gemma":[0.9899668,0.0005565878,0.001817007,0.000706353,0.001933823,0.005019418],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003469433,0.00006316473,0.9607963,0.00002519618,0.0002014846,0.003596857,0.0009395378,0.0002816592,0.0001652102,0.0001119142,0.01415847,0.01962552],"study_design_scores_gemma":[0.00225676,0.0006912561,0.9499381,0.0020565,0.00005515294,0.008297412,0.001160355,0.0001809721,0.001018688,0.0001477,0.03319225,0.001004828],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9617162,0.001370535,0.01820407,0.01099416,0.004696687,0.0001840119,0.0001501242,0.00001311686,0.002671052],"genre_scores_gemma":[0.9925036,0.00004509639,0.005326923,0.001054684,0.0006007677,0.000002523716,0.000002514515,0.00006186235,0.0004020474],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03078733,"threshold_uncertainty_score":0.9999431,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008925560660451838,"score_gpt":0.2723769519893965,"score_spread":0.2634513913289446,"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."}}